Learning-associated functional plasticity at hippocampal synapses remains largely unexplored. Here, in a single session of reward-based trace conditioning, we examine learning-induced synaptic plasticity in the dorsal...Learning-associated functional plasticity at hippocampal synapses remains largely unexplored. Here, in a single session of reward-based trace conditioning, we examine learning-induced synaptic plasticity in the dorsal CA1 hippocampus (dCA1). Local field-potential recording combined with selective optogenetic inhibition first revealed an increase of dCA1 synaptic responses to the conditioned stimulus (CS) induced during conditioning at both Schaffer collaterals to the stratum radiatum (Rad) and temporoammonic input to the lacunosum moleculare (LMol). At these dCA1 inputs, synaptic potentiation of CS-responding excitatory synapses was further demonstrated by locally blocking NMDA receptors during conditioning and whole-cell recording sensory-evoked synaptic responses in dCA1 neurons from naive animals. An overall similar time course of the induction of synaptic potentiation was found in the Rad and LMol by multiple-site recording;this emerged later and saturated earlier than conditioned behavioral responses. Our experiments demonstrate a cued memory-associated dCA1 synaptic plasticity induced at both Schaffer collaterals and temporoammonic pathways.展开更多
Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture,making it a current research hotspot.Due to advantag...Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture,making it a current research hotspot.Due to advantages such as nonvolatility,high density,low power consumption,and high response ratio,memristors are regarded as devices with promising applications in brain-inspired intelligence.This paper proposes a physical Ag/HfO_(x)/FeO_(x)/Pt memristor model.The Ag/HfO_(x)/FeO_(x)/Pt memristor is first fabricated using magnetron sputtering,and its internal principles and characteristics are then thoroughly analyzed.Furthermore,we construct a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72%for the physical memristor.We design a fully functional Pavlovian associative memory circuit,realizing functions including generalization,primary differentiation,secondary differentiation,and forgetting.Finally,the circuit is validated through PSPICE simulation and analysis.展开更多
This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can ...This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.展开更多
The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-rel...The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.展开更多
In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the opti...In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.展开更多
Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only f...Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.展开更多
Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memor...Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.展开更多
The multiple classifier system （MCS）, composed of multiple diverse classifiers or feed-forward neural networks, can significantly improve the classification or generalization ability of a single classifier. Enlighte...The multiple classifier system （MCS）, composed of multiple diverse classifiers or feed-forward neural networks, can significantly improve the classification or generalization ability of a single classifier. Enlightened by the fundamental idea of MCS, the ensemble is introduced into the quick learning for bidirectional associative memory （QLBAM） to construct a BAM ensemble, for improving the storage capacity and the error-correction capability without destroying the simple structure of the component BAM. Simulations show that, with an appropriate ＂overproduce and choose＂ strategy or ＂thinning＂ algorithm, the proposed BAM ensemble significantly outperforms the single QLBAM in both storage capacity and noise-tolerance capability.展开更多
Language is the vehicle of culture, vocabulary is the most active part of a language. This article compares and analyses the relationship of cultural context and the associative meaning of words in three aspects—asso...Language is the vehicle of culture, vocabulary is the most active part of a language. This article compares and analyses the relationship of cultural context and the associative meaning of words in three aspects—associative meaning overlap, associative meaning mismatch and associative meaning gap, revealing its importance in the cross-cultural communication.展开更多
Colors are endowed into many different associative meanings by different peoples and countries under the various cultural backgrounds and people make it express testimonial and depreciated meaning. There is not only t...Colors are endowed into many different associative meanings by different peoples and countries under the various cultural backgrounds and people make it express testimonial and depreciated meaning. There is not only the same aspect, but also the differences. Moreover, some factors such as geographical environment, public sentiment custom, thinking mode, religious belief, and national psychology also influence it. Each kind of color is regarded the difference for every nation's person. This article analyzes and investigates the associative meaning of the color in the Chinese and English cultures. And then it will let the reader learn well and more the associative meaning under the different cultural background.展开更多
Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The exi...Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.展开更多
In this paper the globally asymptotic stability of more general two-layer nonlinear feedback associative memory neural networks with time delays is examined. The sufficient conditions of existence, uniqueness and glob...In this paper the globally asymptotic stability of more general two-layer nonlinear feedback associative memory neural networks with time delays is examined. The sufficient conditions of existence, uniqueness and globally asymptotic stability of the equilibrum position are given. Finally, two interesting examples to illustrate the theory are given.展开更多
Paired associative stimulation is a relatively new non-invasive brain stimulation technique that combines transcranial magnetic stimulation and peripheral nerve stimulation. The effects of paired associative stimulati...Paired associative stimulation is a relatively new non-invasive brain stimulation technique that combines transcranial magnetic stimulation and peripheral nerve stimulation. The effects of paired associative stimulation on the excitability of the cerebral cortex can vary according to the time interval between the transcranial magnetic stimulation and peripheral nerve stimulation. We established a model of cerebral ischemia in rats via transient middle cerebral artery occlusion. We administered paired associative stimulation with a frequency of 0.05 Hz 90 times over 4 weeks. We then evaluated spatial learning and memory using the Morris water maze. Changes in the cerebral ultra-structure and synaptic plasticity were assessed via transmission electron microscopy and a 64-channel multi-electrode array. We measured mRNA and protein expression levels of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1 in the hippocampus using a real-time polymerase chain reaction and western blot assay. Paired associative stimulation treatment significantly improved learning and memory in rats subjected to cerebral ischemia. The ultra-structures of synapses in the CA1 area of the hippocampus in rats subjected to cerebral ischemia were restored by paired associative stimulation. Long-term potentiation at synapses in the CA3 and CA1 regions of the hippocampus was enhanced as well. The protein and mRNA expression of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1 increased after paired associative stimulation treatment. These data indicate that paired associative stimulation can protect cog-nition after cerebral ischemia. The observed effect may be mediated by increases in the mRNA and protein expression of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1, and by enhanced synaptic plasticity in the CA1 area of the hippocampus. The animal experiments were approved by the Animal Ethics Committee of Tongji Medical College, Huazhong University of Science & Technology, China(approval No. TJ-A20151102) on July 11, 2015.展开更多
Paired associative stimulation (PAS),combining transcranial magnetic stimulation (TMS) with electrical peripheral nerve stimulation (PNS) in pairs with an optimal interstimulus interval (ISI)in between,has been shown ...Paired associative stimulation (PAS),combining transcranial magnetic stimulation (TMS) with electrical peripheral nerve stimulation (PNS) in pairs with an optimal interstimulus interval (ISI)in between,has been shown to influence the excitability of the motor cortex (MC)in humans.However,the underlying mechanisms remain unclear.This study was designed to explore an optimal protocol of PAS,which can modulate the excitability of MC in rats,and to investigate the underlying mechanisms. The resting motor thresholds (RMTs) of TMS-elicited motor evoked potentials (MEPs) recorded from the gastrocnemius muscle and the latency of P1 component of somatosensory evoked potentials (SEPs) induced by electrical tibial nerve stimulation were determined in male Sprague-Dawley rats (n=10).Sixty rats were then randomly divided into 3 groups:a PAS group (further divided into 10 subgroups at various ISIs calculated by using the latency of P1,n=5,respectively),a TMS (only)group (n=5)and a PNS (only)group (n=5).Ninety repetitions of PAS,TMS and PNS were administered to the rats in the 3 groups,respectively,at the frequency of 0.05 Hz and the intensity of TMS at 120% RMT and that of PNS at 6 mA.RMTs and motor evoked potentials'amplitude (MEPamp)were recorded before and immediately after the interventions.It was found that the MEPamp significantly decreased after PAS at ISI of 5 ms (P<0.05),while the MEPamp significantly increased after PAS at ISI of 15ms,as compared with those before the intervention (P<0.05).However,the RMT did not change significantly after PAS at ISI of 5 ms or 15 ms (P>0.05).PAS at other ISis as well as the sole use of TMS and PNS induced no remarkable changes in MEPamp and RMT.In conclusion,PAS can influence motor cortex excitability in rats.Neither TMS alone nor PNS alone shows significant effect.展开更多
In this paper, the global exponential stability of an equilibrium position for general bidirectional associative memory neural networks are studied. The sufficient conditions of existence and uniqueness of the equilib...In this paper, the global exponential stability of an equilibrium position for general bidirectional associative memory neural networks are studied. The sufficient conditions of existence and uniqueness of the equilibrium position are given. The method of energy function is examined. Two examples are given to illustrate the theory.展开更多
Alkali-soluble associative latex thickeners modified with hydrophobic long chain alkyl groups were prepared using common acrylics and varying amount of a functional monomer,ethoxylated behenyl methacrylate(BEM),throug...Alkali-soluble associative latex thickeners modified with hydrophobic long chain alkyl groups were prepared using common acrylics and varying amount of a functional monomer,ethoxylated behenyl methacrylate(BEM),through emulsion polymerization.It was found that the size of the emulsion particle became larger with addition of BEM.The light transmittance of the thickener latex sharply increased with pH varied from 6 to 7.The associative latex thickener manifested a higher viscosity when solids in the latex thickeners were kept at 0.5 wt%or higher,and the optimal amount of BEM was found to be around 2.5 wt%,or 0.16 mol%.All thickener latexes modified with BEM have better shearing resistance than the BEM-free thickener.展开更多
Learning to associate a positive or negative experience with an unrelated cue after the presentation of a reward or a punishment defines associative learning.The ability to form associative memories has been reported ...Learning to associate a positive or negative experience with an unrelated cue after the presentation of a reward or a punishment defines associative learning.The ability to form associative memories has been reported in animal species as complex as humans and as simple as insects and sea slugs.Associative memory has even been reported in tardigrades[1],species that diverged from other animal phyla 500 million years ago.Understanding the mechanisms of memory formation is a fundamental goal of neuroscience research.In this article,we work on resolving the current contradictions between different Drosophila associative memory circuit models and propose an updated version of the circuit model that predicts known memory behaviors that current models do not.Finally,we propose a model for how dopamine may function as a reward prediction error signal in Drosophila,a dopamine function that is well-established in mammals but not in insects[2,3].展开更多
The recent progress of non-covalent associative structure of coal, and the mechanisms of the CS2/NMP (1:1 by volume) mixed solvent and the additive addition enhancing the extraction yield of coals were reviewed, and t...The recent progress of non-covalent associative structure of coal, and the mechanisms of the CS2/NMP (1:1 by volume) mixed solvent and the additive addition enhancing the extraction yield of coals were reviewed, and the aggregation behavior of coal in solid and solution states were presented, and the aggregation behavior of coal in solid and solution states were introduced in this paper. Coal extraction and swelling in organic solvents at room temperature were the most useful methods to understand the associative structure of coal. CS2/NMP (1:1 by volume) is a unique solvent to give high extraction yields for some bituminous coals. Some additives can dissociate the stronger interactions among coal molecules and enhance the extraction yields of coal in the mixed solvent.展开更多
A series of hydrophobically associating polyacrylamides modified by small amounts （〈 3 mol%） of a self- associative cationic monomer 4-（2-（acryloyloxy） ethoxy） benzyl tri-ethyl ammonium bromide （AEBA） as hydr...A series of hydrophobically associating polyacrylamides modified by small amounts （〈 3 mol%） of a self- associative cationic monomer 4-（2-（acryloyloxy） ethoxy） benzyl tri-ethyl ammonium bromide （AEBA） as hydrophobe were synthesized by radical copolymerization in aqueous solutions without external surfactants. The resulting eopolymers containing a multiblock structure exhibited a high tendency for hydrophobic association and a high thickening capacity. Solution properties and aggregation structures were investigated by viscometry and fluorescence technique. The high viscosity enhancement was found as the polymer concentration beyond a critical value c＊ and strongly depended on the copolymer microstructures. The number and length of hydrophobic microblocks within the copolymer backbones could be controlled by changing the AEBA concentration in copolymerization system. Addition of salt induced more hydrophobic association and viscosity enhancement. The synthesis method used was simple and environmentally friendly without any external surfactant contamination in comparison with the conventional micellar copolymerization.展开更多
The industrial manufacture of ammonia(NH_(3))using Fe-based catalyst works under rigorous conditions.For the goal of carbon-neutrality,it is highly desired to develop advanced catalyst for NH_(3)synthesis at mild cond...The industrial manufacture of ammonia(NH_(3))using Fe-based catalyst works under rigorous conditions.For the goal of carbon-neutrality,it is highly desired to develop advanced catalyst for NH_(3)synthesis at mild conditions to reduce energy consumption and CO_(2)emissions.However,the main challenge of NH_(3)synthesis at mild conditions lies in the dissociation of steady N≡N triple bond.In this work,we report the design of subnanometer Ru clusters(0.8 nm)anchored on the hollow N-doped carbon spheres catalyst(Ru-SNCs),which effectively promotes the NH_(3)synthesis at mild conditions via an associative route.The NH_(3)synthesis rate over Ru-SNCs(0.49%(mass)Ru)reaches up to 11.7 mmol NH_(3)·(g cat)^(-1)·h^(-1) at 400℃ and 3 MPa,which is superior to that of 8.3 mmol NH_(3)·(g cat)^(-1)·h^(-1) over Ru nanoparticle catalyst(1.20%(mass)Ru).Various characterizations show that the N_(2)H_(4)species are the main intermediates for NH_(3)synthesis on Ru-SNCs catalyst.It demonstrates that Ru-SNCs catalyst can follow an associative route for N_(2)activation,which circumvents the direct dissociation of N_(2)and results in highly efficient NH_(3)synthesis at mild conditions.展开更多
基金supported by grants from the National Natural Science Foundation of China(31970957 and 31471078)the Shanghai Science and Technology Commission(19ZR1416600)a 2021-JCJQ-JJ-1089 fund.
文摘Learning-associated functional plasticity at hippocampal synapses remains largely unexplored. Here, in a single session of reward-based trace conditioning, we examine learning-induced synaptic plasticity in the dorsal CA1 hippocampus (dCA1). Local field-potential recording combined with selective optogenetic inhibition first revealed an increase of dCA1 synaptic responses to the conditioned stimulus (CS) induced during conditioning at both Schaffer collaterals to the stratum radiatum (Rad) and temporoammonic input to the lacunosum moleculare (LMol). At these dCA1 inputs, synaptic potentiation of CS-responding excitatory synapses was further demonstrated by locally blocking NMDA receptors during conditioning and whole-cell recording sensory-evoked synaptic responses in dCA1 neurons from naive animals. An overall similar time course of the induction of synaptic potentiation was found in the Rad and LMol by multiple-site recording;this emerged later and saturated earlier than conditioned behavioral responses. Our experiments demonstrate a cued memory-associated dCA1 synaptic plasticity induced at both Schaffer collaterals and temporoammonic pathways.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62476230 and 61976246)the Natural Science Foundation of Chongqing(Grant No.CSTB2023NSCQ-MSX0018)Fundamental Research Funds for the Central Universities(Grant No.SWUKR22046)。
文摘Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture,making it a current research hotspot.Due to advantages such as nonvolatility,high density,low power consumption,and high response ratio,memristors are regarded as devices with promising applications in brain-inspired intelligence.This paper proposes a physical Ag/HfO_(x)/FeO_(x)/Pt memristor model.The Ag/HfO_(x)/FeO_(x)/Pt memristor is first fabricated using magnetron sputtering,and its internal principles and characteristics are then thoroughly analyzed.Furthermore,we construct a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72%for the physical memristor.We design a fully functional Pavlovian associative memory circuit,realizing functions including generalization,primary differentiation,secondary differentiation,and forgetting.Finally,the circuit is validated through PSPICE simulation and analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.62376105,12101208,and 61906072)the Fundamental Research Funds for the Central Universities(Grant No.2662022XXQD001).
文摘This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.
基金supported by National Natural Science Foundation of China(Grant No.62071377,62101442,62201456)Natural Science Foundation of Shaanxi Province(Grant No.2023-YBGY-036,2022JQ-687)The Graduate Student Innovation Foundation Project of Xi’an University of Posts and Telecommunications under Grant CXJJDL2022003.
文摘The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.
文摘In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.
文摘Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.
文摘Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.
文摘The multiple classifier system （MCS）, composed of multiple diverse classifiers or feed-forward neural networks, can significantly improve the classification or generalization ability of a single classifier. Enlightened by the fundamental idea of MCS, the ensemble is introduced into the quick learning for bidirectional associative memory （QLBAM） to construct a BAM ensemble, for improving the storage capacity and the error-correction capability without destroying the simple structure of the component BAM. Simulations show that, with an appropriate ＂overproduce and choose＂ strategy or ＂thinning＂ algorithm, the proposed BAM ensemble significantly outperforms the single QLBAM in both storage capacity and noise-tolerance capability.
文摘Language is the vehicle of culture, vocabulary is the most active part of a language. This article compares and analyses the relationship of cultural context and the associative meaning of words in three aspects—associative meaning overlap, associative meaning mismatch and associative meaning gap, revealing its importance in the cross-cultural communication.
文摘Colors are endowed into many different associative meanings by different peoples and countries under the various cultural backgrounds and people make it express testimonial and depreciated meaning. There is not only the same aspect, but also the differences. Moreover, some factors such as geographical environment, public sentiment custom, thinking mode, religious belief, and national psychology also influence it. Each kind of color is regarded the difference for every nation's person. This article analyzes and investigates the associative meaning of the color in the Chinese and English cultures. And then it will let the reader learn well and more the associative meaning under the different cultural background.
基金co-supported by the Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (IRT0905)the Step Program of Beijing Key Laboratory (No. Z121104002812053)
文摘Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.
文摘In this paper the globally asymptotic stability of more general two-layer nonlinear feedback associative memory neural networks with time delays is examined. The sufficient conditions of existence, uniqueness and globally asymptotic stability of the equilibrum position are given. Finally, two interesting examples to illustrate the theory are given.
基金supported by the National Natural Science Foundation of China,No.81272156(to TCG)
文摘Paired associative stimulation is a relatively new non-invasive brain stimulation technique that combines transcranial magnetic stimulation and peripheral nerve stimulation. The effects of paired associative stimulation on the excitability of the cerebral cortex can vary according to the time interval between the transcranial magnetic stimulation and peripheral nerve stimulation. We established a model of cerebral ischemia in rats via transient middle cerebral artery occlusion. We administered paired associative stimulation with a frequency of 0.05 Hz 90 times over 4 weeks. We then evaluated spatial learning and memory using the Morris water maze. Changes in the cerebral ultra-structure and synaptic plasticity were assessed via transmission electron microscopy and a 64-channel multi-electrode array. We measured mRNA and protein expression levels of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1 in the hippocampus using a real-time polymerase chain reaction and western blot assay. Paired associative stimulation treatment significantly improved learning and memory in rats subjected to cerebral ischemia. The ultra-structures of synapses in the CA1 area of the hippocampus in rats subjected to cerebral ischemia were restored by paired associative stimulation. Long-term potentiation at synapses in the CA3 and CA1 regions of the hippocampus was enhanced as well. The protein and mRNA expression of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1 increased after paired associative stimulation treatment. These data indicate that paired associative stimulation can protect cog-nition after cerebral ischemia. The observed effect may be mediated by increases in the mRNA and protein expression of brain-derived neurotrophic factor and N-methyl-D-aspartate receptor 1, and by enhanced synaptic plasticity in the CA1 area of the hippocampus. The animal experiments were approved by the Animal Ethics Committee of Tongji Medical College, Huazhong University of Science & Technology, China(approval No. TJ-A20151102) on July 11, 2015.
基金This study was supported by the National Natural Science Foundation of China (No.81272156).
文摘Paired associative stimulation (PAS),combining transcranial magnetic stimulation (TMS) with electrical peripheral nerve stimulation (PNS) in pairs with an optimal interstimulus interval (ISI)in between,has been shown to influence the excitability of the motor cortex (MC)in humans.However,the underlying mechanisms remain unclear.This study was designed to explore an optimal protocol of PAS,which can modulate the excitability of MC in rats,and to investigate the underlying mechanisms. The resting motor thresholds (RMTs) of TMS-elicited motor evoked potentials (MEPs) recorded from the gastrocnemius muscle and the latency of P1 component of somatosensory evoked potentials (SEPs) induced by electrical tibial nerve stimulation were determined in male Sprague-Dawley rats (n=10).Sixty rats were then randomly divided into 3 groups:a PAS group (further divided into 10 subgroups at various ISIs calculated by using the latency of P1,n=5,respectively),a TMS (only)group (n=5)and a PNS (only)group (n=5).Ninety repetitions of PAS,TMS and PNS were administered to the rats in the 3 groups,respectively,at the frequency of 0.05 Hz and the intensity of TMS at 120% RMT and that of PNS at 6 mA.RMTs and motor evoked potentials'amplitude (MEPamp)were recorded before and immediately after the interventions.It was found that the MEPamp significantly decreased after PAS at ISI of 5 ms (P<0.05),while the MEPamp significantly increased after PAS at ISI of 15ms,as compared with those before the intervention (P<0.05).However,the RMT did not change significantly after PAS at ISI of 5 ms or 15 ms (P>0.05).PAS at other ISis as well as the sole use of TMS and PNS induced no remarkable changes in MEPamp and RMT.In conclusion,PAS can influence motor cortex excitability in rats.Neither TMS alone nor PNS alone shows significant effect.
基金Supported by the National Natural Science Foundation of China
文摘In this paper, the global exponential stability of an equilibrium position for general bidirectional associative memory neural networks are studied. The sufficient conditions of existence and uniqueness of the equilibrium position are given. The method of energy function is examined. Two examples are given to illustrate the theory.
文摘Alkali-soluble associative latex thickeners modified with hydrophobic long chain alkyl groups were prepared using common acrylics and varying amount of a functional monomer,ethoxylated behenyl methacrylate(BEM),through emulsion polymerization.It was found that the size of the emulsion particle became larger with addition of BEM.The light transmittance of the thickener latex sharply increased with pH varied from 6 to 7.The associative latex thickener manifested a higher viscosity when solids in the latex thickeners were kept at 0.5 wt%or higher,and the optimal amount of BEM was found to be around 2.5 wt%,or 0.16 mol%.All thickener latexes modified with BEM have better shearing resistance than the BEM-free thickener.
文摘Learning to associate a positive or negative experience with an unrelated cue after the presentation of a reward or a punishment defines associative learning.The ability to form associative memories has been reported in animal species as complex as humans and as simple as insects and sea slugs.Associative memory has even been reported in tardigrades[1],species that diverged from other animal phyla 500 million years ago.Understanding the mechanisms of memory formation is a fundamental goal of neuroscience research.In this article,we work on resolving the current contradictions between different Drosophila associative memory circuit models and propose an updated version of the circuit model that predicts known memory behaviors that current models do not.Finally,we propose a model for how dopamine may function as a reward prediction error signal in Drosophila,a dopamine function that is well-established in mammals but not in insects[2,3].
基金Supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars of MOE and the Natural Scientific Foundation of Anhui Education Department (2003kj052)
文摘The recent progress of non-covalent associative structure of coal, and the mechanisms of the CS2/NMP (1:1 by volume) mixed solvent and the additive addition enhancing the extraction yield of coals were reviewed, and the aggregation behavior of coal in solid and solution states were presented, and the aggregation behavior of coal in solid and solution states were introduced in this paper. Coal extraction and swelling in organic solvents at room temperature were the most useful methods to understand the associative structure of coal. CS2/NMP (1:1 by volume) is a unique solvent to give high extraction yields for some bituminous coals. Some additives can dissociate the stronger interactions among coal molecules and enhance the extraction yields of coal in the mixed solvent.
文摘A series of hydrophobically associating polyacrylamides modified by small amounts （〈 3 mol%） of a self- associative cationic monomer 4-（2-（acryloyloxy） ethoxy） benzyl tri-ethyl ammonium bromide （AEBA） as hydrophobe were synthesized by radical copolymerization in aqueous solutions without external surfactants. The resulting eopolymers containing a multiblock structure exhibited a high tendency for hydrophobic association and a high thickening capacity. Solution properties and aggregation structures were investigated by viscometry and fluorescence technique. The high viscosity enhancement was found as the polymer concentration beyond a critical value c＊ and strongly depended on the copolymer microstructures. The number and length of hydrophobic microblocks within the copolymer backbones could be controlled by changing the AEBA concentration in copolymerization system. Addition of salt induced more hydrophobic association and viscosity enhancement. The synthesis method used was simple and environmentally friendly without any external surfactant contamination in comparison with the conventional micellar copolymerization.
基金the Key Research&Development Program of National Natural Science Foundation of China(22038002)the National Natural Science Foundation of China(21972019,22108037)。
文摘The industrial manufacture of ammonia(NH_(3))using Fe-based catalyst works under rigorous conditions.For the goal of carbon-neutrality,it is highly desired to develop advanced catalyst for NH_(3)synthesis at mild conditions to reduce energy consumption and CO_(2)emissions.However,the main challenge of NH_(3)synthesis at mild conditions lies in the dissociation of steady N≡N triple bond.In this work,we report the design of subnanometer Ru clusters(0.8 nm)anchored on the hollow N-doped carbon spheres catalyst(Ru-SNCs),which effectively promotes the NH_(3)synthesis at mild conditions via an associative route.The NH_(3)synthesis rate over Ru-SNCs(0.49%(mass)Ru)reaches up to 11.7 mmol NH_(3)·(g cat)^(-1)·h^(-1) at 400℃ and 3 MPa,which is superior to that of 8.3 mmol NH_(3)·(g cat)^(-1)·h^(-1) over Ru nanoparticle catalyst(1.20%(mass)Ru).Various characterizations show that the N_(2)H_(4)species are the main intermediates for NH_(3)synthesis on Ru-SNCs catalyst.It demonstrates that Ru-SNCs catalyst can follow an associative route for N_(2)activation,which circumvents the direct dissociation of N_(2)and results in highly efficient NH_(3)synthesis at mild conditions.
