The Experts below are selected from a list of 59892 Experts worldwide ranked by ideXlab platform
Fuat Balcı - One of the best experts on this subject based on the ideXlab platform.
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Spontaneous integration of temporal information: implications for representational/Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.
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spontaneous integration of temporal information implications for representational Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.
Ezgi Gür - One of the best experts on this subject based on the ideXlab platform.
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Spontaneous integration of temporal information: implications for representational/Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.
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spontaneous integration of temporal information implications for representational Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.
Barak A. Pearlmutter - One of the best experts on this subject based on the ideXlab platform.
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COLT - VC dimension of an integrate-and-fire neuron model
Proceedings of the ninth annual conference on Computational learning theory - COLT '96, 1996Co-Authors: Anthony M. Zador, Barak A. PearlmutterAbstract:We compute the VC dimension of a leaky integrate-and-fire neuron model. The VC dimension quantifies the ability of a function class to partition an input pattern space, and can be considered a measure of Computational Capacity. In this case, the function class is the class of integrate-and-fire models generated by varying the integration time constant T and the threshold θ, the input space they partition is the space of continuous-time signals, and the binary partition is specified by whether or not the model reaches threshold at some specified time. We show that the VC dimension diverges only logarithmically with the input signal bandwidth N. We also extend this approach to arbitrary passive dendritic trees. The main contributions of this work are (1) it offers a novel treatment of Computational Capacity of this class of dynamic system; and (2) it provides a framework for analyzing the Computational capabilities of the dynamic systems defined by networks of spiking neurons.
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Vc dimension of an integrate-and-fire neuron model
Neural Computation, 1996Co-Authors: Anthony M. Zador, Barak A. PearlmutterAbstract:We compute the VC dimension of a leaky integrate-and-fire neuron model. The VC dimension quantifies the ability of a function class to partition an input pattern space, and can be considered a measure of Computational Capacity. In this case, the function class is the class of integrate-and-fire models generated by varying the integration time constant T and the threshold θ, the input space they partition is the space of continuous-time signals, and the binary partition is specified by whether or not the model reaches threshold at some specified time. We show that the VC dimension diverges only logarithmically with the input signal bandwidth N. We also extend this approach to arbitrary passive dendritic trees. The main contributions of this work are (1) it offers a novel treatment of Computational Capacity of this class of dynamic system; and (2) it provides a framework for analyzing the Computational capabilities of the dynamic systems defined by networks of spiking neurons.
S Imre - One of the best experts on this subject based on the ideXlab platform.
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Hash-Based Mutual Authentication Protocol for Low-Cost RFID Systems
2012Co-Authors: Gyozo Godor, S ImreAbstract:In the last decade RFID technology has become widespread. It can be found in various fields of our daily life. Due to the rapid development more and more security problems were raised. Since tags have limited memory and very low Computational Capacity a so-called lightweight authentication is needed. Several protocols have been proposed to resolve security and privacy issues in RFID systems. However, the earlier suggested algorithms do not satisfy all of the security requirements.In this paper we introduce our hash-based mutual authentication protocol which meets all the security requirements. Our solution provides an efficient mutual authentication method. Our protocol can defy the well-known attacks and does not demand high Computational Capacity.
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elliptic curve cryptography based authentication protocol for small Computational Capacity rfid systems
Proceedings of the 6th ACM workshop on QoS and security for wireless and mobile networks, 2010Co-Authors: Győző Goodor, Peter Szendi, S ImreAbstract:In the last few years RFID technology widespread. This technology can be found in each field of our daily life, e.g. supply-chain management, libraries, access management etc. For the sake of small Computational Capacity of RFID Tags, at first, only mathematical and logical operations and lightweight authentication methods can be used. However, thanks to the evolution of RFID technology, nowadays PKI infrastructure is also usable in this environment. In this paper we present our elliptic curve cryptography based authentication protocol which protects against the well-known attacks. We give a brief comparison with other EC based protocols in the security point of view.
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elliptic curve cryptography based mutual authentication protocol for low Computational Capacity rfid systems performance analysis by simulations
Wireless Communications Networking and Information Security, 2010Co-Authors: Gyozo Godor, Norbert Giczi, S ImreAbstract:RFID technology can be found in the most fields of our daily life, e.g. personal identification, supply-chain management, access control etc. For the sake of small Computational Capacity of RFID Tags, at first, only mathematical and logical operations and lightweight authentication methods could be used. However, thanks to the evolution of RFID technology, nowadays PKI infrastructure is also usable in this environment. In this paper we present our elliptic curve cryptography based mutual authentication protocol which proofs against the well-known attacks. We give a brief comparison with other EC based protocols in the point of view of security. Moreover, we show that our protocol is better than the others in case of performance, too. In order to measure the performance characteristics of our proposed ECC based authentication protocol and to make a comparison with others we implemented these algorithms in OMNeT++.
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Q2SWinet - Elliptic curve cryptography based authentication protocol for small Computational Capacity RFID systems
Proceedings of the 6th ACM workshop on QoS and security for wireless and mobile networks - Q2SWinet '10, 2010Co-Authors: Győző Goodor, Peter Szendi, S ImreAbstract:In the last few years RFID technology widespread. This technology can be found in each field of our daily life, e.g. supply-chain management, libraries, access management etc. For the sake of small Computational Capacity of RFID Tags, at first, only mathematical and logical operations and lightweight authentication methods can be used. However, thanks to the evolution of RFID technology, nowadays PKI infrastructure is also usable in this environment. In this paper we present our elliptic curve cryptography based authentication protocol which protects against the well-known attacks. We give a brief comparison with other EC based protocols in the security point of view.
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WCNIS - Elliptic curve cryptography based mutual authentication protocol for low Computational Capacity RFID systems - performance analysis by simulations
2010 IEEE International Conference on Wireless Communications Networking and Information Security, 2010Co-Authors: Gyozo Godor, Norbert Giczi, S ImreAbstract:RFID technology can be found in the most fields of our daily life, e.g. personal identification, supply-chain management, access control etc. For the sake of small Computational Capacity of RFID Tags, at first, only mathematical and logical operations and lightweight authentication methods could be used. However, thanks to the evolution of RFID technology, nowadays PKI infrastructure is also usable in this environment. In this paper we present our elliptic curve cryptography based mutual authentication protocol which proofs against the well-known attacks. We give a brief comparison with other EC based protocols in the point of view of security. Moreover, we show that our protocol is better than the others in case of performance, too. In order to measure the performance characteristics of our proposed ECC based authentication protocol and to make a comparison with others we implemented these algorithms in OMNeT++.
Yalçın Akın Duyan - One of the best experts on this subject based on the ideXlab platform.
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Spontaneous integration of temporal information: implications for representational/Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.
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spontaneous integration of temporal information implications for representational Computational Capacity of animals
Animal Cognition, 2018Co-Authors: Ezgi Gür, Yalçın Akın Duyan, Fuat BalcıAbstract:How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/Computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.