This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of r...This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of reasoning--System 1 that is unconscious, associative, implicit, more emotional and less controlled, and so forth; and System 2 that is conscious, explicit, deliberate and rule-governed, and so forth. The benefits of the proposed model that integrates these two complementary and compensatory systems are first illustrated with an example in audit planning, and second explained how the model could overcome the deficiencies of heuristics specifically in an audit context.展开更多
The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenti...The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. From 2012, the journal enters into IEEE Xplore Digital Library with the open access mode. In 2015, Tsinghua Science and Technology has been indexed in the Science Citation Index Expanded with IF 1.250.展开更多
The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to de...The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.展开更多
The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to de...The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.展开更多
The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach ...The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach and integrating a machine consciousness mechanism based on Global Workspace Theory,MECA has been updated to integrate a dual-layer subsumption mechanism,enabling both reactive and deliberative behaviors,dynamic goal setting and a visual-spatial memory subsystem,enhancing MECA’s capacity for real-world interaction and adaptive behavior.Also,with the introduction of the new computational ideas’knowledge representation scheme,MECA proposes to organize knowledge dynamically to handle context-sensitive reasoning and flexible categorization.MECA’s implementation relies on the Cognitive Systems Toolkit(CST),facilitating its integration with cutting-edge technologies.MECA and CST are being continuously developed and updated,aligned,and open to incorporate the latest AI artifacts and methodologies.This approach ensures the delivery of organized,monitorable,auditable,and controllable AI solutions,significantly reducing reliance on“black box”cognitive processes while enhancing transparency and accountability in AI-driven systems.These updates reinforce MECA’s potential as a robust architecture for developing autonomous,adaptable,and context-aware AI systems capable of real-world interaction and adaptive learning.展开更多
Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent an...Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent and mathematical foundations of autonomous systems.It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems.It explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive process.The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering.Emerging paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are described.Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.展开更多
The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive syste...The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.展开更多
Second language acquisition can not be understood without addressing the interaction between language and cognition. Cognitive theory can extend to describe learning strategies as complex cognitive skills. Theoretical...Second language acquisition can not be understood without addressing the interaction between language and cognition. Cognitive theory can extend to describe learning strategies as complex cognitive skills. Theoretical developments in Anderson’s production systems cover a broader range of behavior than other theories, including comprehension and production of oral and written texts as well as comprehension, problem solving, and verbal learning.Thus Anderson’s cognitive theory can be served as a rationale for learning strategy studies in second language acquisition.展开更多
By cognitive radio,the low Earth orbit（LEO） satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks...By cognitive radio,the low Earth orbit（LEO） satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks（CRNs）.The competition can be regarded as a game and analyzed with game theory.This particular unlicensed spectrum sharing problem is modeled here,and the special properties of ＂spatially-distinguished-interference＂ and the short period of the interactions between satellites and terrestrial CRNs are explored.Then,the problem is formulated as a ＂partially-blind＂ finitely repeated prisoner＇s dilemma by game theory.Finally,we begin with two promising spectrum sharing schemes,which can be used to enforce the frequency reuse among the remotely located terrestrial CRN players as well as to overcome the observation noise.By analysis and comparison,it is proposed that the novel refreshing-contrite-tit-for-tat（R-CTFT） is the optimal spectrum sharing scheme.Simulation results verify that it can be used to utilize the spectrum most efficiently.展开更多
Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent object...Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA （Defense Advanced Research Projects Agency） as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the loT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the loT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current stan dardization activities are surveyed and discussed to the ensure the security of loT components and applications.展开更多
This paper investigates the performance of an underlay cognitive relay system where secondary users（SUs） suffer from a primary outage probability constraint and spectrum-sharing interference imposed by a primary use...This paper investigates the performance of an underlay cognitive relay system where secondary users（SUs） suffer from a primary outage probability constraint and spectrum-sharing interference imposed by a primary user（PU）. In particular, we consider a secondary multi-relay network operating in the selection decode-and-forward（SDF） mode and propose a best-relay selection criterion which takes into account the spectrum-sharing constraint and interference. Based on these assumptions, the closed-form expression of the outage probability of secondary transmissions is derived. We find that a floor of the outage probability occurs in high signal-to-noise ratio（SNR） regions due to the joint effect of the constraint and the interference from the PU. In addition, we propose a generalized definition of the diversity gain for such systems and show that a full diversity order is achieved. Simulation results verify our theoretical solutions.展开更多
As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio （CR） system in...As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio （CR） system in which CR users may access the spectrum allocated to primary users （PUs）. Particularly, the channel between the CR transmitter （CR-T） and the primary receiver and the channel between the CR-T and the CR receiver （CR-R） may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service （QoS） constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.展开更多
Purpose-The purpose of this paper is to proposes a forward search algorithm for detecting and identifying natural structures arising in human-computer interaction(HCI)and human physiological response(HPR)data.Design/m...Purpose-The purpose of this paper is to proposes a forward search algorithm for detecting and identifying natural structures arising in human-computer interaction(HCI)and human physiological response(HPR)data.Design/methodology/approach-The paper portrays aspects that are essential to modelling and precision in detection.The methods involves developed algorithm for detecting outliers in data to recognise natural patterns in incessant data such as HCI-HPR data.The detected categorical data are simultaneously labelled based on the data reliance on parametric rules to predictive models used in classification algorithms.Data were also simulated based on multivariate normal distribution method and used to compare and validate the original data.Findings-Results shows that the forward search method provides robust features that are capable of repelling over-fitting in physiological and eye movement data.Research limitations/implications-One of the limitations of the robust forward search algorithm is that when the number of digits for residuals value is more than the expected size for stack flow,it normally yields an error caution;to counter this,the data sets are normally standardized by taking the logarithmic function of the model before running the algorithm.Practical implications-The authors conducted some of the experiments at individual residence which may affect environmental constraints.Originality/value-The novel approach to this method is the detection of outliers for data sets based on the Mahalanobis distances on HCI and HPR.And can also involve a large size of data with p possible parameters.The improvement made to the algorithm is application of more graphical display and rendering of the residual plot.展开更多
Purpose–The purpose of this paper is to present a new approach to edge detection using semiconductor flash memory networks having scalable and parallel hardware architecture.Design/methodology/approach–A flash cell ...Purpose–The purpose of this paper is to present a new approach to edge detection using semiconductor flash memory networks having scalable and parallel hardware architecture.Design/methodology/approach–A flash cell can store multiple states by controlling its voltage threshold.The equivalent resistance of the operation states controlled by threshold voltage of flash cell gives out different combinations of logic 0 and 1 states.The paper explores this basic feature of flash memory in designing a resistance change memory network for implementing novel edge detector hardware.This approach of detecting the edges is inspired from the spatial change detection ability of the human visual system.Findings–The proposed approach consumes less number of electronic components for its implementation,and outperforms the conventional approaches of edge detection with respect to the processing speed,scalability and ease of design.It is also demonstrated to provide edges invariant to changes in the direction of the spatial change in the images.Research limitations/implications–This research brings about a new direction in the development of edge detection,in terms of developing high-speed parallel processing edge detection and imaging circuits.Practical implications–The proposed approach reduces the implementation complexity by removing the need to have convolution operations for spatial edge filtering.Originality/value–This paper presents one of the first edge detection approaches that is purely a hardware oriented design,uses resistance of flash memory to form edge detector cells,and one that does not use computational operations such as additions or multiplications for its implementation.展开更多
文摘This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of reasoning--System 1 that is unconscious, associative, implicit, more emotional and less controlled, and so forth; and System 2 that is conscious, explicit, deliberate and rule-governed, and so forth. The benefits of the proposed model that integrates these two complementary and compensatory systems are first illustrated with an example in audit planning, and second explained how the model could overcome the deficiencies of heuristics specifically in an audit context.
文摘The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. From 2012, the journal enters into IEEE Xplore Digital Library with the open access mode. In 2015, Tsinghua Science and Technology has been indexed in the Science Citation Index Expanded with IF 1.250.
基金This work was funded by the EPSRC Grant"Improving the product development process through integrated revision control and twinning of digital-physical models during prototyping",reference:EP/R032696/1.
文摘The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.
文摘The digital twin is often presented as the solution to Industry 4.0 and,while there are many areas where this may be the case,there is a risk that a reliance on existing machine learning methods will not be able to deliver the high level cognitive capabilities such as adaptability,cause and effect,and planning that Industry 4.0 requires.As the limitations of machine learning are beginning to be understood,the paradigm of strong artificial intelligence is emerging.The field of artificial cognitive systems is part of the strong artificial intelligence paradigm and is aimed at generating computational systems capable of mimicking biological systems in learning and interacting with the world.This paper presents an argument that artificial cognitive systems offer solutions to the higher level cognitive challenges of Industry 4.0 and that digital twin research should be driven in the direction of artificial cognition accordingly.This argument is based on the inherent similarities between the digital twin and artificial cognitive systems,and the insights that can already be seen in aligning the two approaches.
基金Supported by the Sao Paulo Research Foundation(FAPESP),CPE SMARTNESS(2021/00199-8)and CEPID/BRAINN(2013/07559-3).
文摘The Multipurpose Enhanced Cognitive Architecture(MECA)is a cognitive framework designed to model complex,human-like processes across multiple domains.Originally focusing on implementing a Dual Process Theory approach and integrating a machine consciousness mechanism based on Global Workspace Theory,MECA has been updated to integrate a dual-layer subsumption mechanism,enabling both reactive and deliberative behaviors,dynamic goal setting and a visual-spatial memory subsystem,enhancing MECA’s capacity for real-world interaction and adaptive behavior.Also,with the introduction of the new computational ideas’knowledge representation scheme,MECA proposes to organize knowledge dynamically to handle context-sensitive reasoning and flexible categorization.MECA’s implementation relies on the Cognitive Systems Toolkit(CST),facilitating its integration with cutting-edge technologies.MECA and CST are being continuously developed and updated,aligned,and open to incorporate the latest AI artifacts and methodologies.This approach ensures the delivery of organized,monitorable,auditable,and controllable AI solutions,significantly reducing reliance on“black box”cognitive processes while enhancing transparency and accountability in AI-driven systems.These updates reinforce MECA’s potential as a robust architecture for developing autonomous,adaptable,and context-aware AI systems capable of real-world interaction and adaptive learning.
基金supported in part by the Department of National Defence’s Innovation for Defence Excellence and Security(IDEa S)Program,Canadathrough the Project of Auto Defence Towards Trustworthy Technologies for Autonomous Human-Machine Systems,NSERCthe IEEE SMC Society Technical Committee on Brain-Inspired Systems(TCBCS)。
文摘Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent and mathematical foundations of autonomous systems.It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems.It explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive process.The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering.Emerging paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are described.Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.
文摘The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.
文摘Second language acquisition can not be understood without addressing the interaction between language and cognition. Cognitive theory can extend to describe learning strategies as complex cognitive skills. Theoretical developments in Anderson’s production systems cover a broader range of behavior than other theories, including comprehension and production of oral and written texts as well as comprehension, problem solving, and verbal learning.Thus Anderson’s cognitive theory can be served as a rationale for learning strategy studies in second language acquisition.
文摘By cognitive radio,the low Earth orbit（LEO） satellites may prefer to operate in the unlicensed spectrum which is open to all the users,and compete for the limited resources with terrestrial cognitive radio networks（CRNs）.The competition can be regarded as a game and analyzed with game theory.This particular unlicensed spectrum sharing problem is modeled here,and the special properties of ＂spatially-distinguished-interference＂ and the short period of the interactions between satellites and terrestrial CRNs are explored.Then,the problem is formulated as a ＂partially-blind＂ finitely repeated prisoner＇s dilemma by game theory.Finally,we begin with two promising spectrum sharing schemes,which can be used to enforce the frequency reuse among the remotely located terrestrial CRN players as well as to overcome the observation noise.By analysis and comparison,it is proposed that the novel refreshing-contrite-tit-for-tat（R-CTFT） is the optimal spectrum sharing scheme.Simulation results verify that it can be used to utilize the spectrum most efficiently.
文摘Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA （Defense Advanced Research Projects Agency） as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the loT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the loT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current stan dardization activities are surveyed and discussed to the ensure the security of loT components and applications.
基金supported by the National Nature Science Foundation of China(51204145)the Science and Technology Research and Development Program of Qinhuangdao(201302A033)
文摘This paper investigates the performance of an underlay cognitive relay system where secondary users（SUs） suffer from a primary outage probability constraint and spectrum-sharing interference imposed by a primary user（PU）. In particular, we consider a secondary multi-relay network operating in the selection decode-and-forward（SDF） mode and propose a best-relay selection criterion which takes into account the spectrum-sharing constraint and interference. Based on these assumptions, the closed-form expression of the outage probability of secondary transmissions is derived. We find that a floor of the outage probability occurs in high signal-to-noise ratio（SNR） regions due to the joint effect of the constraint and the interference from the PU. In addition, we propose a generalized definition of the diversity gain for such systems and show that a full diversity order is achieved. Simulation results verify our theoretical solutions.
基金supported by the National Natural Science Foundation of China (61171029)
文摘As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio （CR） system in which CR users may access the spectrum allocated to primary users （PUs）. Particularly, the channel between the CR transmitter （CR-T） and the primary receiver and the channel between the CR-T and the CR receiver （CR-R） may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service （QoS） constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.
基金And also the Petroleum Technology Develop Fund Nigeria(PTDF)for sponsoring this research.
文摘Purpose-The purpose of this paper is to proposes a forward search algorithm for detecting and identifying natural structures arising in human-computer interaction(HCI)and human physiological response(HPR)data.Design/methodology/approach-The paper portrays aspects that are essential to modelling and precision in detection.The methods involves developed algorithm for detecting outliers in data to recognise natural patterns in incessant data such as HCI-HPR data.The detected categorical data are simultaneously labelled based on the data reliance on parametric rules to predictive models used in classification algorithms.Data were also simulated based on multivariate normal distribution method and used to compare and validate the original data.Findings-Results shows that the forward search method provides robust features that are capable of repelling over-fitting in physiological and eye movement data.Research limitations/implications-One of the limitations of the robust forward search algorithm is that when the number of digits for residuals value is more than the expected size for stack flow,it normally yields an error caution;to counter this,the data sets are normally standardized by taking the logarithmic function of the model before running the algorithm.Practical implications-The authors conducted some of the experiments at individual residence which may affect environmental constraints.Originality/value-The novel approach to this method is the detection of outliers for data sets based on the Mahalanobis distances on HCI and HPR.And can also involve a large size of data with p possible parameters.The improvement made to the algorithm is application of more graphical display and rendering of the residual plot.
文摘Purpose–The purpose of this paper is to present a new approach to edge detection using semiconductor flash memory networks having scalable and parallel hardware architecture.Design/methodology/approach–A flash cell can store multiple states by controlling its voltage threshold.The equivalent resistance of the operation states controlled by threshold voltage of flash cell gives out different combinations of logic 0 and 1 states.The paper explores this basic feature of flash memory in designing a resistance change memory network for implementing novel edge detector hardware.This approach of detecting the edges is inspired from the spatial change detection ability of the human visual system.Findings–The proposed approach consumes less number of electronic components for its implementation,and outperforms the conventional approaches of edge detection with respect to the processing speed,scalability and ease of design.It is also demonstrated to provide edges invariant to changes in the direction of the spatial change in the images.Research limitations/implications–This research brings about a new direction in the development of edge detection,in terms of developing high-speed parallel processing edge detection and imaging circuits.Practical implications–The proposed approach reduces the implementation complexity by removing the need to have convolution operations for spatial edge filtering.Originality/value–This paper presents one of the first edge detection approaches that is purely a hardware oriented design,uses resistance of flash memory to form edge detector cells,and one that does not use computational operations such as additions or multiplications for its implementation.
