The rapid development of brain-like neural networks and secure data transmission technologies has placed greater demands on highly complex neural network systems and highly secure encryption methods.To this end,the pa...The rapid development of brain-like neural networks and secure data transmission technologies has placed greater demands on highly complex neural network systems and highly secure encryption methods.To this end,the paper proposes a novel high-dimensional memristor synapse-coupled hyperchaotic neural network by using the designed memristor as the synapse to connect an inertial neuron(IN)and a Hopfield neural network(HNN).By using numerical tools including bifurcation plots,phase plots,and basins of attraction,it is found that the dynamics of this system are closely related to the memristor coupling strength,self-connection synaptic weights,and inter-connection synaptic weights,and it can exhibit excellent hyperchaotic behaviors and coexisting multi-stable patterns.Through PSIM circuit simulations,the complex dynamics of the coupled IN-HNN system are verified.Furthermore,a DNA-encoded encryption algorithm is given,which utilizes generated hyperchaotic sequences to achieve encoding,operation,and decoding of DNA.The results show that this algorithm possesses strong robustness against statistical attacks,differential attacks,and noise interference,and can effectively resist known/selected plaintext attacks.This work will provide new ideas for the modeling of large-scale brainlike neural networks and high-security image encryption.展开更多
Neural synchronization is associated with various brain disorders,making it essential to investigate the intrinsic factors that influence the synchronization of coupled neural networks.In this paper,we propose a minim...Neural synchronization is associated with various brain disorders,making it essential to investigate the intrinsic factors that influence the synchronization of coupled neural networks.In this paper,we propose a minimal architecture as a prototype,consisting of two bi-neuron Hopfield neural networks(HNNs)coupled via a memristor.This coupling elevates the original two bi-neuron HNNs into a five-dimensional system,featuring an unstable line equilibrium set and rich dynamics absent in the uncoupled case.Our results show that varying the coupling strength and the initial state of the memristor can induce periodic,chaotic,hyperchaotic,and quasi-periodic oscillations,as well as initial-offset-regulated multistability.We derive sufficient conditions for achieving exponential synchronization and identify multiple synchronous regimes with transitions that strongly depend on the initial states.Field-programmable gate array(FPGA)implementation confirms the predicted dynamics and synchronization in real time,demonstrating that the memristive coupler enables complex dynamics and controllable synchronization in the most compact Hopfield architecture,with implications for the study of neuromorphic circuits and synchronization.展开更多
Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, ...Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, 2018 to December 31, 2019, in patients with acute leukemia in the Oncohematology department of the National Hospital of Niamey (HNN), whose diagnosis was made on a blood smear associated with a myelogram and immunophenotyping and who were consenting. Results: We collected 25 cases of acute leukemia confirmed by myelogram and immunophenotyping. The mean age of the patients was 31.32 years, with a predominance of women, a sex ratio of 0.92. Pupils and students were in the majority with 40% and most came from the Niamey region, i.e. 68%. Anemic syndrome was the most common clinical sign in 96%. ALL predominated in 64% of cases. On the blood count, the hyperleukocytosis was more marked in AML (mean white count: 197256.6 elts/mm3) than in ALL (137891.6 elts/mm3), it was the same for thrombocytopenia which is more marked in AML (75588.89/mm3) than in ALL (52156.25/mm3). Therapeutically, 52% of patients received chemotherapy. The mean overall survival was 16.223 ± 3.191 months, including a mean survival for AML of 6.853 ± 1200 months compared to 21.720 ± 5.920 months for ALL. Conclusion: Acute leukemia still remains a major problem in our context, due to the precariousness of limited financial, diagnostic and therapeutic resources. Thus reflecting in our results, the increasing number of cases, the diagnostic delay and the guarded prognosis. This is the reality in several other countries in the sub-region and even in certain developed countries.展开更多
A new approach to fault dignosis dealing with nonlinear system Hopfieldneural networks (HNN) is presented. The model parameters of the nonlinear systemtreated as functions of measured operating points and faults are e...A new approach to fault dignosis dealing with nonlinear system Hopfieldneural networks (HNN) is presented. The model parameters of the nonlinear systemtreated as functions of measured operating points and faults are estimated by HNN. Boththe nominal model of the healthy system and HNN training models corresponding to everyoperating point are recognized. In addition, the anticipated fault models corresponding toevery kind of fault and every operating point are obtaind in advance. The real systemmodel parameters of the system estimated by generalization process of HNN are matchedwith the nominal models of the healthy system and anticipated fault models. Consequent-ly, the final result of fault detection and diagnosis is acquired. The approach to fault diag-nosis is used in an aircraft actuating poisition servo system and the simulation resu1t is re-ported.展开更多
A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network(HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the s...A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network(HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral(MS) image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.展开更多
基金Project supported by the Training Plan of Young Backbone Teachers in Universities of Henan Province(Grant No.2023GGJS142)the Key Scientific Research of Colleges and Universities in Henan Province,China(Grant No.25A120009)+1 种基金Changzhou Leading Innovative Talent Introduction and Cultivation Project(Grant No.CQ20240102)Changzhou Applied Basic Research Program(Grant No.CJ20253065)。
文摘The rapid development of brain-like neural networks and secure data transmission technologies has placed greater demands on highly complex neural network systems and highly secure encryption methods.To this end,the paper proposes a novel high-dimensional memristor synapse-coupled hyperchaotic neural network by using the designed memristor as the synapse to connect an inertial neuron(IN)and a Hopfield neural network(HNN).By using numerical tools including bifurcation plots,phase plots,and basins of attraction,it is found that the dynamics of this system are closely related to the memristor coupling strength,self-connection synaptic weights,and inter-connection synaptic weights,and it can exhibit excellent hyperchaotic behaviors and coexisting multi-stable patterns.Through PSIM circuit simulations,the complex dynamics of the coupled IN-HNN system are verified.Furthermore,a DNA-encoded encryption algorithm is given,which utilizes generated hyperchaotic sequences to achieve encoding,operation,and decoding of DNA.The results show that this algorithm possesses strong robustness against statistical attacks,differential attacks,and noise interference,and can effectively resist known/selected plaintext attacks.This work will provide new ideas for the modeling of large-scale brainlike neural networks and high-security image encryption.
基金supported by the National Natural Science Foundation of China(Grant No.62271088)the Qinglan Project of Jiangsu Province+2 种基金the Jiangsu Government Scholarship for Overseas Studiesthe Training Plan of Young Backbone Teachers in Universities of Henan Province(Grant No.2023GGJS142)the Key Scientific Research of Colleges and Universities in Henan Province(Grant No.25A120009)。
文摘Neural synchronization is associated with various brain disorders,making it essential to investigate the intrinsic factors that influence the synchronization of coupled neural networks.In this paper,we propose a minimal architecture as a prototype,consisting of two bi-neuron Hopfield neural networks(HNNs)coupled via a memristor.This coupling elevates the original two bi-neuron HNNs into a five-dimensional system,featuring an unstable line equilibrium set and rich dynamics absent in the uncoupled case.Our results show that varying the coupling strength and the initial state of the memristor can induce periodic,chaotic,hyperchaotic,and quasi-periodic oscillations,as well as initial-offset-regulated multistability.We derive sufficient conditions for achieving exponential synchronization and identify multiple synchronous regimes with transitions that strongly depend on the initial states.Field-programmable gate array(FPGA)implementation confirms the predicted dynamics and synchronization in real time,demonstrating that the memristive coupler enables complex dynamics and controllable synchronization in the most compact Hopfield architecture,with implications for the study of neuromorphic circuits and synchronization.
文摘Objective: Improve the care of patients followed for acute leukemia in the Oncohematology department of the National Hospital of Niamey. Methods: This was a prospective study, over a period of 2 years from January 1, 2018 to December 31, 2019, in patients with acute leukemia in the Oncohematology department of the National Hospital of Niamey (HNN), whose diagnosis was made on a blood smear associated with a myelogram and immunophenotyping and who were consenting. Results: We collected 25 cases of acute leukemia confirmed by myelogram and immunophenotyping. The mean age of the patients was 31.32 years, with a predominance of women, a sex ratio of 0.92. Pupils and students were in the majority with 40% and most came from the Niamey region, i.e. 68%. Anemic syndrome was the most common clinical sign in 96%. ALL predominated in 64% of cases. On the blood count, the hyperleukocytosis was more marked in AML (mean white count: 197256.6 elts/mm3) than in ALL (137891.6 elts/mm3), it was the same for thrombocytopenia which is more marked in AML (75588.89/mm3) than in ALL (52156.25/mm3). Therapeutically, 52% of patients received chemotherapy. The mean overall survival was 16.223 ± 3.191 months, including a mean survival for AML of 6.853 ± 1200 months compared to 21.720 ± 5.920 months for ALL. Conclusion: Acute leukemia still remains a major problem in our context, due to the precariousness of limited financial, diagnostic and therapeutic resources. Thus reflecting in our results, the increasing number of cases, the diagnostic delay and the guarded prognosis. This is the reality in several other countries in the sub-region and even in certain developed countries.
文摘A new approach to fault dignosis dealing with nonlinear system Hopfieldneural networks (HNN) is presented. The model parameters of the nonlinear systemtreated as functions of measured operating points and faults are estimated by HNN. Boththe nominal model of the healthy system and HNN training models corresponding to everyoperating point are recognized. In addition, the anticipated fault models corresponding toevery kind of fault and every operating point are obtaind in advance. The real systemmodel parameters of the system estimated by generalization process of HNN are matchedwith the nominal models of the healthy system and anticipated fault models. Consequent-ly, the final result of fault detection and diagnosis is acquired. The approach to fault diag-nosis is used in an aircraft actuating poisition servo system and the simulation resu1t is re-ported.
文摘A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network(HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral(MS) image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.
