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Emergent Neural Computational Architectures Based on Neuroscience [[electronic resource] ] : Towards Neuroscience-Inspired Computing / / edited by Stefan Wermter, Jim Austin, David Willshaw
| Emergent Neural Computational Architectures Based on Neuroscience [[electronic resource] ] : Towards Neuroscience-Inspired Computing / / edited by Stefan Wermter, Jim Austin, David Willshaw |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (X, 582 p.) |
| Disciplina | 006.3/2 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Algorithms Pattern recognition Neurology Neurosciences Artificial Intelligence Computation by Abstract Devices Algorithm Analysis and Problem Complexity Pattern Recognition Neurology |
| ISBN | 3-540-44597-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Towards Novel Neuroscience-Inspired Computing -- Towards Novel Neuroscience-Inspired Computing -- Modular Organisation and Robustness -- Images of the Mind: Brain Images and Neural Networks -- Stimulus-Independent Data Analysis for fMRI -- Emergence of Modularity within One Sheet of Neurons: A Model Comparison -- Computational Investigation of Hemispheric Specialization and Interactions -- Explorations of the Interaction between Split Processing and Stimulus Types -- Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization -- Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System -- Recurrent Long-Range Interactions in Early Vision -- Neural Mechanisms for Representing Surface and Contour Features -- Representations of Neuronal Models Using Minimal and Bilinear Realisations -- Collaborative Cell Assemblies: Building Blocks of Cortical Computation -- On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex -- Towards Computational Neural Systems through Developmental Evolution -- The Complexity of the Brain: Structural, Functional, and Dynamic Modules -- Timing and Synchronisation -- Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission -- Segmenting State into Entities and Its Implication for Learning -- Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain -- Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle -- Locust Olfaction -- Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays -- The Role of Brain Chaos -- Neural Network Classification of Word Evoked Neuromagnetic Brain Activity -- Simulation Studies of the Speed of Recurrent Processing -- Learning and Memory Storage -- The Dynamics of Learning and Memory: Lessons from Neuroscience -- Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation -- Plasticity and Nativism: Towards a Resolution of an Apparent Paradox -- Cell Assemblies as an Intermediate Level Model of Cognition -- Modelling Higher Cognitive Functions with Hebbian Cell Assemblies -- Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity -- A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex -- Linguistic Computation with State Space Trajectories -- Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission -- Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models? -- An Investigation into the Role of Cortical Synaptic Depression in Auditory Processing -- The Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics -- Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots -- Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System -- Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources -- Connectionist Neuroimaging. |
| Record Nr. | UNINA-9910143597803321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Emergent Neural Computational Architectures Based on Neuroscience [[electronic resource] ] : Towards Neuroscience-Inspired Computing / / edited by Stefan Wermter, Jim Austin, David Willshaw
| Emergent Neural Computational Architectures Based on Neuroscience [[electronic resource] ] : Towards Neuroscience-Inspired Computing / / edited by Stefan Wermter, Jim Austin, David Willshaw |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (X, 582 p.) |
| Disciplina | 006.3/2 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Algorithms Pattern recognition Neurology Neurosciences Artificial Intelligence Computation by Abstract Devices Algorithm Analysis and Problem Complexity Pattern Recognition Neurology |
| ISBN | 3-540-44597-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Towards Novel Neuroscience-Inspired Computing -- Towards Novel Neuroscience-Inspired Computing -- Modular Organisation and Robustness -- Images of the Mind: Brain Images and Neural Networks -- Stimulus-Independent Data Analysis for fMRI -- Emergence of Modularity within One Sheet of Neurons: A Model Comparison -- Computational Investigation of Hemispheric Specialization and Interactions -- Explorations of the Interaction between Split Processing and Stimulus Types -- Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization -- Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System -- Recurrent Long-Range Interactions in Early Vision -- Neural Mechanisms for Representing Surface and Contour Features -- Representations of Neuronal Models Using Minimal and Bilinear Realisations -- Collaborative Cell Assemblies: Building Blocks of Cortical Computation -- On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex -- Towards Computational Neural Systems through Developmental Evolution -- The Complexity of the Brain: Structural, Functional, and Dynamic Modules -- Timing and Synchronisation -- Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission -- Segmenting State into Entities and Its Implication for Learning -- Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain -- Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle -- Locust Olfaction -- Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays -- The Role of Brain Chaos -- Neural Network Classification of Word Evoked Neuromagnetic Brain Activity -- Simulation Studies of the Speed of Recurrent Processing -- Learning and Memory Storage -- The Dynamics of Learning and Memory: Lessons from Neuroscience -- Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation -- Plasticity and Nativism: Towards a Resolution of an Apparent Paradox -- Cell Assemblies as an Intermediate Level Model of Cognition -- Modelling Higher Cognitive Functions with Hebbian Cell Assemblies -- Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity -- A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex -- Linguistic Computation with State Space Trajectories -- Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission -- Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models? -- An Investigation into the Role of Cortical Synaptic Depression in Auditory Processing -- The Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics -- Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots -- Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System -- Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources -- Connectionist Neuroimaging. |
| Record Nr. | UNISA-996465780703316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolvable Systems: From Biology to Hardware [[electronic resource] ] : 9th International Conference, ICES 2010, York, UK, September 6-8, 2010, Proceedings / / edited by Gianluca Tempesti, Andy Tyrrell, Julian F. Miller
| Evolvable Systems: From Biology to Hardware [[electronic resource] ] : 9th International Conference, ICES 2010, York, UK, September 6-8, 2010, Proceedings / / edited by Gianluca Tempesti, Andy Tyrrell, Julian F. Miller |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (XII, 394 p. 228 illus.) |
| Disciplina | 006.3/2 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Software engineering
Computer science Computer networks Artificial intelligence Computers, Special purpose Software Engineering Theory of Computation Computer Communication Networks Artificial Intelligence Computer Science Logic and Foundations of Programming Special Purpose and Application-Based Systems |
| ISBN |
1-280-38849-8
9786613566416 3-642-15323-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Session 1: Evolving Digital Circuits -- Measuring the Performance and Intrinsic Variability of Evolved Circuits -- An Efficient Selection Strategy for Digital Circuit Evolution -- Introducing Flexibility in Digital Circuit Evolution: Exploiting Undefined Values in Binary Truth Tables -- Evolving Digital Circuits Using Complex Building Blocks -- Session 2: Artificial Development -- Fault Tolerance of Embryonic Algorithms in Mobile Networks -- Evolution and Analysis of a Robot Controller Based on a Gene Regulatory Network -- A New Method to Find Developmental Descriptions for Digital Circuits -- Sorting Network Development Using Cellular Automata -- Session 3: GPU Platforms for Bio-inspired Algorithms -- Markerless Articulated Human Body Tracking from Multi-view Video with GPU-PSO -- Evolving Object Detectors with a GPU Accelerated Vision System -- Systemic Computation Using Graphics Processors -- Session 4: Implementations and Applications of Neural Networks -- An Efficient, High-Throughput Adaptive NoC Router for Large Scale Spiking Neural Network Hardware Implementations -- Performance Evaluation and Scaling of a Multiprocessor Architecture Emulating Complex SNN Algorithms -- Evolution of Analog Circuit Models of Ion Channels -- HyperNEAT for Locomotion Control in Modular Robots -- Session 5: Test, Repair and Reconfiguration Using Evolutionary Algorithms -- The Use of Genetic Algorithm to Reduce Power Consumption during Test Application -- Designing Combinational Circuits with an Evolutionary Algorithm Based on the Repair Technique -- Bio-inspired Self-testing Configurable Circuits -- Evolutionary Design of Reconfiguration Strategies to Reduce the Test Application Time -- Session 6: Applications of Evolutionary Algorithms in Hardware -- Extrinsic Evolution of Fuzzy Systems Applied to Disease Diagnosis -- Automatic Code Generation on a MOVE Processor Using Cartesian Genetic Programming -- Coping with Resource Fluctuations: The Run-time Reconfigurable Functional Unit Row Classifier Architecture -- Session 7: Reconfigurable Hardware Platforms -- A Self-reconfigurable FPGA-Based Platform for Prototyping Future Pervasive Systems -- The X2 Modular Evolutionary Robotics Platform -- Ubichip, Ubidule, and MarXbot: A Hardware Platform for the Simulation of Complex Systems -- Implementation of a Power-Aware Dynamic Fault Tolerant Mechanism on the Ubichip Platform -- Session 8: Applications of Evolution to Technology -- Automatic Synthesis of Lossless Matching Networks -- A Novel Approach to Multi-level Evolutionary Design Optimization of a MEMS Device -- From Binary to Continuous Gates – and Back Again -- Adaptive vs. Self-adaptive Parameters for Evolving Quantum Circuits -- Session 9: Novel Methods in Evolutionary Design -- Imitation Programming -- EvoFab: A Fully Embodied Evolutionary Fabricator -- Evolving Physical Self-assembling Systems in Two-Dimensions. |
| Record Nr. | UNISA-996465966103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolvable Systems: From Biology to Hardware [[electronic resource] ] : 9th International Conference, ICES 2010, York, UK, September 6-8, 2010, Proceedings / / edited by Gianluca Tempesti, Andy Tyrrell, Julian F. Miller
| Evolvable Systems: From Biology to Hardware [[electronic resource] ] : 9th International Conference, ICES 2010, York, UK, September 6-8, 2010, Proceedings / / edited by Gianluca Tempesti, Andy Tyrrell, Julian F. Miller |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (XII, 394 p. 228 illus.) |
| Disciplina | 006.3/2 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Software engineering
Computer science Computer networks Artificial intelligence Computers, Special purpose Software Engineering Theory of Computation Computer Communication Networks Artificial Intelligence Computer Science Logic and Foundations of Programming Special Purpose and Application-Based Systems |
| ISBN |
1-280-38849-8
9786613566416 3-642-15323-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Session 1: Evolving Digital Circuits -- Measuring the Performance and Intrinsic Variability of Evolved Circuits -- An Efficient Selection Strategy for Digital Circuit Evolution -- Introducing Flexibility in Digital Circuit Evolution: Exploiting Undefined Values in Binary Truth Tables -- Evolving Digital Circuits Using Complex Building Blocks -- Session 2: Artificial Development -- Fault Tolerance of Embryonic Algorithms in Mobile Networks -- Evolution and Analysis of a Robot Controller Based on a Gene Regulatory Network -- A New Method to Find Developmental Descriptions for Digital Circuits -- Sorting Network Development Using Cellular Automata -- Session 3: GPU Platforms for Bio-inspired Algorithms -- Markerless Articulated Human Body Tracking from Multi-view Video with GPU-PSO -- Evolving Object Detectors with a GPU Accelerated Vision System -- Systemic Computation Using Graphics Processors -- Session 4: Implementations and Applications of Neural Networks -- An Efficient, High-Throughput Adaptive NoC Router for Large Scale Spiking Neural Network Hardware Implementations -- Performance Evaluation and Scaling of a Multiprocessor Architecture Emulating Complex SNN Algorithms -- Evolution of Analog Circuit Models of Ion Channels -- HyperNEAT for Locomotion Control in Modular Robots -- Session 5: Test, Repair and Reconfiguration Using Evolutionary Algorithms -- The Use of Genetic Algorithm to Reduce Power Consumption during Test Application -- Designing Combinational Circuits with an Evolutionary Algorithm Based on the Repair Technique -- Bio-inspired Self-testing Configurable Circuits -- Evolutionary Design of Reconfiguration Strategies to Reduce the Test Application Time -- Session 6: Applications of Evolutionary Algorithms in Hardware -- Extrinsic Evolution of Fuzzy Systems Applied to Disease Diagnosis -- Automatic Code Generation on a MOVE Processor Using Cartesian Genetic Programming -- Coping with Resource Fluctuations: The Run-time Reconfigurable Functional Unit Row Classifier Architecture -- Session 7: Reconfigurable Hardware Platforms -- A Self-reconfigurable FPGA-Based Platform for Prototyping Future Pervasive Systems -- The X2 Modular Evolutionary Robotics Platform -- Ubichip, Ubidule, and MarXbot: A Hardware Platform for the Simulation of Complex Systems -- Implementation of a Power-Aware Dynamic Fault Tolerant Mechanism on the Ubichip Platform -- Session 8: Applications of Evolution to Technology -- Automatic Synthesis of Lossless Matching Networks -- A Novel Approach to Multi-level Evolutionary Design Optimization of a MEMS Device -- From Binary to Continuous Gates – and Back Again -- Adaptive vs. Self-adaptive Parameters for Evolving Quantum Circuits -- Session 9: Novel Methods in Evolutionary Design -- Imitation Programming -- EvoFab: A Fully Embodied Evolutionary Fabricator -- Evolving Physical Self-assembling Systems in Two-Dimensions. |
| Record Nr. | UNINA-9910483088603321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Flexible neuro-fuzzy systems : structures, learning, and performance evaluation / / by Leszek Rutkowski
| Flexible neuro-fuzzy systems : structures, learning, and performance evaluation / / by Leszek Rutkowski |
| Autore | Rutkowski Leszek |
| Pubbl/distr/stampa | Springer US |
| Disciplina | 006.3/2 |
| Soggetto topico |
Neural networks (Computer science)
Fuzzy systems |
| ISBN | 1-4020-8043-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910783442003321 |
Rutkowski Leszek
|
||
| Springer US | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Flexible neuro-fuzzy systems : structures, learning, and performance evaluation / / by Leszek Rutkowski
| Flexible neuro-fuzzy systems : structures, learning, and performance evaluation / / by Leszek Rutkowski |
| Autore | Rutkowski Leszek |
| Pubbl/distr/stampa | Springer US |
| Disciplina | 006.3/2 |
| Soggetto topico |
Neural networks (Computer science)
Fuzzy systems |
| ISBN | 1-4020-8043-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910821048003321 |
|
Rutkowski Leszek
|
||
| Springer US | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor
| Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor |
| Pubbl/distr/stampa | New York, : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (426 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) | FloresJohn A |
| Collana | Mathematics research developments |
| Soggetto topico |
Neural networks (Computer science)
Artificial intelligence |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-61942-100-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""CONTENTS ""; ""PREFACE ""; ""APPLICATION OF ARTIFICIAL NEURAL NETWORKS (ANNS) IN DEVELOPMENT OF PHARMACEUTICAL MICROEMULSIONS ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""3. MICROEMULSIONS ""; ""4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS ""; ""4.1. Prediction of Phase Behaviour ""; ""4.1.1. The influence of ANNs type/architecture ""; ""4.2. Screening of the Microemulsion Constituents ""
""4.3. Prediction of Structural Features of Microemulsions """"5. CONCLUSION ""; ""Symbols and Terminologies ""; ""REFERENCES ""; ""INVESTGATIONS OF APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR FLOW SHOP SCHEDULING PROBLEMS ""; ""ABSTRACT ""; ""1.0 INTRODUCTION ""; ""1.1. Flow Shop Scheduling""; ""1.2. Methodologies used In Flow shop Scheduling ""; ""2.0. ANN APPROACH FOR SCHEDULING A BICRITERION FLOW SHOP ""; ""2.1. Problem Description ""; ""2.2. Architecture of the Proposed System ""; ""2.2.1. Initial learning stage""; ""2.2.2. Implementation stage "" ""2.3. Bidirectional Neural Network Structure """"2.4. An Illustration ""; ""2.5. Results and Discussions ""; ""3.0. ANN APPROACH FOR SCHEDULING A MULTI CRITERION FLOW SHOP""; ""3.1. Illustration ""; ""3.2. Results and Discussions ""; ""4.0. A HYBRID NEURAL NETWORK-META HEURISTIC APPROACH FOR PERMUTATION FLOW SHOP SCHEDULING ""; ""4.1. Introduction ""; ""4.2. Architecture of the ANN ""; ""4.3. Methodology ""; ""4.4. Results and Discussion ""; ""4.4.1. Suliman�s heuristic""; ""4.4.2. Genetic algorithm ""; ""Generation of initial population""; ""4.4.3. Simulated annealing "" ""4.5. Results and Discussions """"4.6. Inferences ""; ""5.0. CONCLUSIONS AND FUTURE DIRECTIONS ""; ""REFERENCES ""; ""ARTIFICIAL NEURAL NETWORKS IN ENVIRONMENTAL SCIENCES AND CHEMICAL ENGINEERING ""; ""ABSTRACT ""; ""INTRODUCTION ""; ""BRIEF DESCRIPTION OF ANN ""; ""LITERATURE REVIEW ""; ""ENVIRONMENTAL SCIENCES ""; ""CHEMICAL ENGINEERING ""; ""Modelling ""; ""Control""; ""Software Sensors ""; ""CONCLUSIONS ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES ""; ""ESTABLISHING PRODUCTIVITY INDICES FOR WHEAT IN THE ARGENTINE PAMPAS BY AN ARTIFICIAL NEURAL NETWORK APPROACH""; ""ABSTRACT "" ""ENVIRONMENTAL FACTORS CONTROLLING WHEAT YIELD IN THE PAMPAS """"Attempts for Predicting Wheat Yield in the Pampas Using Regression Techniques ""; ""Use of Artificial Neural Networks to Predict Wheat Yield ""; ""Establishing Productivity Indices by an Artificial Neural Network Approach""; ""CONCLUDING REMARKS""; ""REFERENCES ""; ""DESIGN OF ARTIFICIAL NEURAL NETWORK PREDICTORS IN MECHANICAL SYSTEMS PROBLEMS ""; ""ABSTRACT ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""2.1. Feedforward Neural Networks ""; ""2.2. Recurrent Neural Networks "" ""2.1.1. Back Propagation neural network (BPNN) "" |
| Record Nr. | UNINA-9910457182403321 |
| New York, : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor
| Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor |
| Pubbl/distr/stampa | New York, : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (426 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) | FloresJohn A |
| Collana | Mathematics research developments |
| Soggetto topico |
Neural networks (Computer science)
Artificial intelligence |
| ISBN | 1-61942-100-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""CONTENTS ""; ""PREFACE ""; ""APPLICATION OF ARTIFICIAL NEURAL NETWORKS (ANNS) IN DEVELOPMENT OF PHARMACEUTICAL MICROEMULSIONS ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""3. MICROEMULSIONS ""; ""4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS ""; ""4.1. Prediction of Phase Behaviour ""; ""4.1.1. The influence of ANNs type/architecture ""; ""4.2. Screening of the Microemulsion Constituents ""
""4.3. Prediction of Structural Features of Microemulsions """"5. CONCLUSION ""; ""Symbols and Terminologies ""; ""REFERENCES ""; ""INVESTGATIONS OF APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR FLOW SHOP SCHEDULING PROBLEMS ""; ""ABSTRACT ""; ""1.0 INTRODUCTION ""; ""1.1. Flow Shop Scheduling""; ""1.2. Methodologies used In Flow shop Scheduling ""; ""2.0. ANN APPROACH FOR SCHEDULING A BICRITERION FLOW SHOP ""; ""2.1. Problem Description ""; ""2.2. Architecture of the Proposed System ""; ""2.2.1. Initial learning stage""; ""2.2.2. Implementation stage "" ""2.3. Bidirectional Neural Network Structure """"2.4. An Illustration ""; ""2.5. Results and Discussions ""; ""3.0. ANN APPROACH FOR SCHEDULING A MULTI CRITERION FLOW SHOP""; ""3.1. Illustration ""; ""3.2. Results and Discussions ""; ""4.0. A HYBRID NEURAL NETWORK-META HEURISTIC APPROACH FOR PERMUTATION FLOW SHOP SCHEDULING ""; ""4.1. Introduction ""; ""4.2. Architecture of the ANN ""; ""4.3. Methodology ""; ""4.4. Results and Discussion ""; ""4.4.1. Suliman�s heuristic""; ""4.4.2. Genetic algorithm ""; ""Generation of initial population""; ""4.4.3. Simulated annealing "" ""4.5. Results and Discussions """"4.6. Inferences ""; ""5.0. CONCLUSIONS AND FUTURE DIRECTIONS ""; ""REFERENCES ""; ""ARTIFICIAL NEURAL NETWORKS IN ENVIRONMENTAL SCIENCES AND CHEMICAL ENGINEERING ""; ""ABSTRACT ""; ""INTRODUCTION ""; ""BRIEF DESCRIPTION OF ANN ""; ""LITERATURE REVIEW ""; ""ENVIRONMENTAL SCIENCES ""; ""CHEMICAL ENGINEERING ""; ""Modelling ""; ""Control""; ""Software Sensors ""; ""CONCLUSIONS ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES ""; ""ESTABLISHING PRODUCTIVITY INDICES FOR WHEAT IN THE ARGENTINE PAMPAS BY AN ARTIFICIAL NEURAL NETWORK APPROACH""; ""ABSTRACT "" ""ENVIRONMENTAL FACTORS CONTROLLING WHEAT YIELD IN THE PAMPAS """"Attempts for Predicting Wheat Yield in the Pampas Using Regression Techniques ""; ""Use of Artificial Neural Networks to Predict Wheat Yield ""; ""Establishing Productivity Indices by an Artificial Neural Network Approach""; ""CONCLUDING REMARKS""; ""REFERENCES ""; ""DESIGN OF ARTIFICIAL NEURAL NETWORK PREDICTORS IN MECHANICAL SYSTEMS PROBLEMS ""; ""ABSTRACT ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""2.1. Feedforward Neural Networks ""; ""2.2. Recurrent Neural Networks "" ""2.1.1. Back Propagation neural network (BPNN) "" |
| Record Nr. | UNINA-9910778821903321 |
| New York, : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor
| Focus on artificial neural networks [[electronic resource] /] / John A. Flores, editor |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York, : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (426 p.) |
| Disciplina | 006.3/2 |
| Altri autori (Persone) | FloresJohn A |
| Collana | Mathematics research developments |
| Soggetto topico |
Neural networks (Computer science)
Artificial intelligence |
| ISBN | 1-61942-100-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""FOCUS ON ARTIFICIAL NEURAL NETWORKS ""; ""CONTENTS ""; ""PREFACE ""; ""APPLICATION OF ARTIFICIAL NEURAL NETWORKS (ANNS) IN DEVELOPMENT OF PHARMACEUTICAL MICROEMULSIONS ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""3. MICROEMULSIONS ""; ""4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS ""; ""4.1. Prediction of Phase Behaviour ""; ""4.1.1. The influence of ANNs type/architecture ""; ""4.2. Screening of the Microemulsion Constituents ""
""4.3. Prediction of Structural Features of Microemulsions """"5. CONCLUSION ""; ""Symbols and Terminologies ""; ""REFERENCES ""; ""INVESTGATIONS OF APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR FLOW SHOP SCHEDULING PROBLEMS ""; ""ABSTRACT ""; ""1.0 INTRODUCTION ""; ""1.1. Flow Shop Scheduling""; ""1.2. Methodologies used In Flow shop Scheduling ""; ""2.0. ANN APPROACH FOR SCHEDULING A BICRITERION FLOW SHOP ""; ""2.1. Problem Description ""; ""2.2. Architecture of the Proposed System ""; ""2.2.1. Initial learning stage""; ""2.2.2. Implementation stage "" ""2.3. Bidirectional Neural Network Structure """"2.4. An Illustration ""; ""2.5. Results and Discussions ""; ""3.0. ANN APPROACH FOR SCHEDULING A MULTI CRITERION FLOW SHOP""; ""3.1. Illustration ""; ""3.2. Results and Discussions ""; ""4.0. A HYBRID NEURAL NETWORK-META HEURISTIC APPROACH FOR PERMUTATION FLOW SHOP SCHEDULING ""; ""4.1. Introduction ""; ""4.2. Architecture of the ANN ""; ""4.3. Methodology ""; ""4.4. Results and Discussion ""; ""4.4.1. Suliman�s heuristic""; ""4.4.2. Genetic algorithm ""; ""Generation of initial population""; ""4.4.3. Simulated annealing "" ""4.5. Results and Discussions """"4.6. Inferences ""; ""5.0. CONCLUSIONS AND FUTURE DIRECTIONS ""; ""REFERENCES ""; ""ARTIFICIAL NEURAL NETWORKS IN ENVIRONMENTAL SCIENCES AND CHEMICAL ENGINEERING ""; ""ABSTRACT ""; ""INTRODUCTION ""; ""BRIEF DESCRIPTION OF ANN ""; ""LITERATURE REVIEW ""; ""ENVIRONMENTAL SCIENCES ""; ""CHEMICAL ENGINEERING ""; ""Modelling ""; ""Control""; ""Software Sensors ""; ""CONCLUSIONS ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES ""; ""ESTABLISHING PRODUCTIVITY INDICES FOR WHEAT IN THE ARGENTINE PAMPAS BY AN ARTIFICIAL NEURAL NETWORK APPROACH""; ""ABSTRACT "" ""ENVIRONMENTAL FACTORS CONTROLLING WHEAT YIELD IN THE PAMPAS """"Attempts for Predicting Wheat Yield in the Pampas Using Regression Techniques ""; ""Use of Artificial Neural Networks to Predict Wheat Yield ""; ""Establishing Productivity Indices by an Artificial Neural Network Approach""; ""CONCLUDING REMARKS""; ""REFERENCES ""; ""DESIGN OF ARTIFICIAL NEURAL NETWORK PREDICTORS IN MECHANICAL SYSTEMS PROBLEMS ""; ""ABSTRACT ""; ""1. INTRODUCTION ""; ""2. ARTIFICIAL NEURAL NETWORKS (ANNS) ""; ""2.1. Feedforward Neural Networks ""; ""2.2. Recurrent Neural Networks "" ""2.1.1. Back Propagation neural network (BPNN) "" |
| Record Nr. | UNINA-9910809188703321 |
| New York, : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Gradient expectations : structure, origins, and synthesis of predictive neural networks / / Keith L. Downing
| Gradient expectations : structure, origins, and synthesis of predictive neural networks / / Keith L. Downing |
| Autore | Downing Keith L |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cambridge, MA : , : The MIT Press, , 2023 |
| Descrizione fisica | 1 online resource (280 pages) |
| Disciplina | 006.3/2 |
| Collana | The MIT Press |
| Soggetto topico | Neural networks (Computer science) |
| ISBN |
0-262-37468-4
0-262-37467-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- 1. Introduction -- 1.1. Data from Predictions -- 1.2. Movement and Prediction -- 1.3. Adaptation and Emergence -- 1.3.1. Gradients and Emergence in Neural Networks -- 1.4. Overflowing Expectations -- 2. Conceptual Foundations of Prediction -- 2.1. Compare and Err -- 2.2. Guesses and Goals -- 2.3. Gradients -- 2.3.1. Gradients Rising -- 2.4. Sequences -- 2.5. Abstracting by Averaging -- 2.6. Control and Prediction -- 2.7. Predictive Coding -- 2.8. Tracking Marr's Tiers -- 3. Biological Foundations of Prediction -- 3.1. Gradient-Following Bacteria -- 3.2. Neural Motifs for Gradient Calculation -- 3.3. Birth of a PID Controller -- 3.3.1. Adaptive Control in the Cerebellum -- 3.4. Detectors and Generators -- 3.4.1. The Hippocampus -- 3.4.2. Conceptual Embedding in the Hippocampus -- 3.5. Gradients of Predictions in the Basal Ganglia -- 3.6. Procedural versus Declarative Prediction -- 3.7. Rampant Expectations -- 4. Neural Energy Networks -- 4.1. Energetic Basis of Learning and Prediction -- 4.2. Energy Landscapes and Gradients -- 4.3. The Boltzmann Machine -- 4.4. The Restricted Boltzmann Machine (RBM) -- 4.5. Free Energy -- 4.5.1. Variational Free Energy -- 4.6. The Helmholtz Machine -- 4.7. The Free Energy Principle -- 4.8. Getting a Grip -- 5. Predictive Coding -- 5.1. Information Theory and Perception -- 5.2. Predictive Coding on High -- 5.2.1. Learning Proper Predictions -- 5.3. Predictive Coding for Machine Learning -- 5.3.1. The Backpropagation Algorithm -- 5.3.2. Backpropagation via Predictive Coding -- 5.4. In Theory -- 6. Emergence of Predictive Networks -- 6.1. Facilitated Variation -- 6.2. Origins of Sensorimotor Activity -- 6.2.1. Origins of Oscillations -- 6.2.2. Activity Regulation in the Brain.
6.2.3. Competition and Cooperation in Brain Development -- 6.2.4. Layers and Modules -- 6.2.5. Running through the Woods on an Icy Evening -- 6.2.6. Oscillations and Learning -- 6.3. A Brief Evolutionary History of the Predictive Brain -- 7. Evolving Artificial Predictive Networks -- 7.1. I'm a Doctor, Not a Connectionist -- 7.2. Evolving Artificial Neural Networks (EANNs) -- 7.2.1. Reconciling EANNs with Deep Learning -- 7.3. Evolving Predictive Coding Networks -- 7.3.1. Preserving Backpropagation in a Local Form -- 7.3.2. Phylogenetic, Ontogenetic, and Epigenetic (POE) -- 7.4. Continuous Time Recurrent Neural Networks (CTRNNs) -- 7.4.1. Evolving Minimally Cognitive Agents -- 7.4.2. Cognitive Robots Using Predictive Coding -- 7.4.3. Toward More Emergent CTRNNs -- 7.5. Predictive POE Networks -- 7.5.1. Simulating Neural Selectionism and Constructivism -- 7.5.2. Predictive Constructivism -- 7.5.3. The D'Arcy Model -- 7.5.4. Neurites to Neurons in D'Arcy -- 7.5.5. Peripherals in D'Arcy -- 7.5.6. Neuromodulators in D'Arcy -- 7.5.7. Predictively Unpredictable -- 7.6. Most Useful and Excellent Designs -- 8. Conclusion -- 8.1. Schrodinger's Frozen Duck -- 8.2. Expectations Great and Small -- 8.3. As Expected -- 8.4. Gradient Expectations -- 8.5. Expecting the Unexpected -- References -- Index. |
| Record Nr. | UNINA-9910741380503321 |
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Downing Keith L
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| Cambridge, MA : , : The MIT Press, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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