- Introduction
- Modulated Hebb Learning Rule and Computational Circuit
- Modulated Hebbain Rule: The Case N=K
- Modulated Hebb-Oja Rule: Case N < K
- Introduction of the New PCA Learning Rule
- Simulation Results
- Comparison to a Part of the Frog Retinal Wiring
- Conclusion
- References
Chapter 56 - Orthogonal Shrinkage Methods for Nonparametric Regression under Gaussian Noise
- Introduction
- Formulation
- Regression Problem and Regularized Cost
- Training Via Eigendecomposition of Gram Matrix
- Shrinkage Methods
- Numerical Experiments
- Choice of Regularization Parameter
- Comparison with LOOCV
- Conclusions and Future Works
Chapter 57 - A Subspace Method Based on Data Generation Model with Class Information
- Introduction
- Data Generation Model
- Factor Analysis Based on Data Generation Model
- Intra-class Factor Loading
- Extra-Class Factor Loading
- Experimental Results
- Face Recognition
- Pose Recognition
- Facial Expression Recognition
- Conclusions and Discussions
Chapter 58 - Hierarchical Feature Extraction for Compact Representation and Classification of Datasets
- Introduction
- Hierarchical Feature Extraction
- Hierarchical Clustering
- Extracting a Tree of Significant Clusters
- Obtaining a Tree of Features
- Classification of Feature Trees
- Applications
- Mixtures of Gaussians
- Clinical EEG
- Discussion
Chapter 59 - Principal Component Analysis for Sparse High-Dimensional Data
- Introduction
- Algorithms for Principal Component Analysis
- Principal Component Analysis with Missing Values
- Overfitting
- Experiments
- Discussion
Chapter 60 - Hierarchical Bayesian Inference of Brain Activity
- Introduction
- MEG Inverse Problem
- Hierarchical Bayesian Method
- Resolution Curve
- Visual Experiments
- Conclusion
Chapter 61 - Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models
- Introduction
- Nonlinear Dynamical Model and Neural Decoding
- Global Laplace
- Expectation Propagation
- Results
- Conclusion
Chapter 62 - Estimating Internal Variables of a Decision Maker’s Brain: A Model-Based Approach for Neuroscience
- Introduction
- Reinforcement Leaning Model as an Animal or Human Decision Maker
- Probabilistic Dynamic Evolution of Internal Variable for Q-Learning Agent
- Computational Model-Based Analysis of Brain Activity
- Application to Monkey Choice Behavior and Striatal Neural Activity
- Application to Human Imaging Data
- Conclusion
- References
Chapter 63 - Visual Tracking Achieved by Adaptive Sampling from Hierarchical and Parallel Predictions
- Introduction
- Adaptive Sampling from Hierarchical and Parallel Predictions
- Incremental Bayes and Particle Filtering
- Estimation of Hierarchically-Modeled State Variables
- Application to Pose Estimation of a Rigid Object
- Experiments
- Modeling Primate's Visual Tracking by Particle Filters
- Conclusion
Chapter 64 - Bayesian System Identification of Molecular Cascades
- Introduction
- Problem Setting
- Bayesian System Identification
- Numerical Demonstrations
- Conclusion
Chapter 65 - Use of Circle-Segments as a Data Visualization Technique for Feature Selection in Pattern Classification
- Introduction
- The Circle-Segments Method
- Experiments
- Data Sets
- Iris Classification
- Suspected Acute Stroke Patients
- Summary and Further Work
- References
Chapter 66 - Extraction of Approximate Independent Components from Large Natural Scenes
- Introduction
- LMICA with Recursive MDS
- MaxKurt Algorithm
- Recursive MDS
- Results
- Experimental Settings
- Experimental Results
- Discussion
- Conclusion
Chapter 67 - Local Coordinates Alignment and Its Linearization
- Introduction
- LCA: Local Coordinates Alignment
- Local Representations
- Global Alignment
- LLCA: Linear Local Coordinates Alignment
- Experiments
- Non-linear Dimensionality Reduction Using LCA
- Face Recognition Using LLCA
- Conclusions
- References
Chapter 68 - Walking Appearance Manifolds without Falling Off
- Introduction
- Appearance Manifolds and Embedding
- Mapping between the Spaces
- View Prediction
- Experiments
- Conclusion
Chapter 69 - Inverse-Halftoning for Error Diffusion Based on Statistical Mechanics of the Spin System
- Introduction
- General Formulation
- Performance
- Summary and Discussion
- References
Chapter 70 - Chaotic Motif Sampler for Motif Discovery Using Statistical Values of Spike Time-Series
- Introduction
- Chaotic Motif Sampler
- Statistical Measures CV and LV CvLv
- Results
- Investigation of Statistical Measures of CV and LV
- Multiple Motif Case
- Conclusions
Chapter 71 - A Thermodynamical Search Algorithm for Feature Subset Selection
- Introduction
- Feature Selection
- Simulated Annealing
- TFS: A Thermodynamic Feature Selection Algorithm
- An Experimental Study
- Experimental Setup
- Discussion of the Results
- Computational Cost
- Conclusions
Chapter 72 - Solvable Performances of Optimization Neural Networks with Chaotic Noise and Stochastic Noise with Negative Autocorrelation
- Introduction
- Optimization by Neural Networks with Chaotic Noise
- Negative Autocorrelation Noise
- Conclusion
Chapter 73 - Solving the k-Winners-Take-All Problem and the Oligopoly Cournot-Nash Equilibrium Problem Using the General Projection Neural Networks
- Introduction
- Neural Network Model
- k-Winners-Take-All Network
- Oligopoly Cournot-Nash Equilibrium
- Concluding Remarks
Chapter 74 - Optimization of Parametric Companding Function for an Efficient Coding
- Introduction
- Companding Vector Quantization
- Architecture
- Optimization
- Applications to Transform Coding
- Architecture
- Simulation Results
- Discussion
Chapter 75 - A Modified Soft-Shape-Context ICP Registration System of 3-D Point Data
- Introduction
- Background of ICP Algorithm
- The Approximate K-D Tree Search Algorithm
- The Soft-Shape-Context ICP Registration
- The Proposed Adaptive Registration System
- The Proposed Registration System
- The Adaptive Dual AK-D Tree Search Algorithm
- The Modified Soft-Shape-Context ICP
- Experimental Results
- The Comparisons of ICP with AK-D Tree and ADAK-D Tree
- The Comparisons of ICP, Soft-Shape-Context ICP and the Proposed Algorithm
- Conclusion
- References
Chapter 76 - Solution Method Using Correlated Noise for TSP
- Introduction
- TSP
- Proposed Method
- Simulation Results
- Locations of Cities
- Experimental Procedure
- Results
- Conclusion
Chapter 77 - Bayesian Collaborative Predictors for General User Modeling Tasks
- Introduction
- Bayesian Network
- Bayesian Collaborative Predictors
- Prediction with Individual User Models
- Bayesian Collaboration of Pre-learned Predictors
- Experimental Results
- Printer Usage Data
- Simulation Setting
- Results
- Summary
Chapter 78 - Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes
- Introduction
- LiNGAM
- LiNGAM in the Presence of Latent Classes
- Motivation
- Model
- Model Identification Using ICA Mixtures
- Illustrative Examples
- Simulation
- Conclusion
Chapter 79 - Efficient Incremental Learning Using Self-Organizing Neural Grove
- Introduction
- Self-Organizing Neural Grove
- On-line Pruning of Self-Generating Neural Tree
- Optimization of the SONG
- Simple Example of the Pruning Method
- Experimental Results
- Conclusions
Chapter 80 - Design of an Unsupervised Weight Parameter Estimation Method in Ensemble Learning
- Introduction
- Ensemble Learning with Supervised Weight Parameter Estimation
- Fundamental Model
- General Model Based on the Exponential Mixture Model
- Ensemble Learning with Unsupervised Weight Parameter Estimation
- Motivation
- Proposed Method
- Numerical Examples
- Experimental Conditions
- Results and Discussion
- Conclusion
Chapter 81 - Sparse Super Symmetric Tensor Factorization
- Introduction -- Problem Formulation
- Multiplicative SNTF Algorithms
- Generalized Alpha Divergence
- SMART Algorithm
- Generalized Beta Divergence
- Simple Alternative Approaches for Super-Symmetric Tensor Decomposition
- Averaging Approach
- Row-Wise and Column-Wise Unfolding Approach
- Semi-orthogonality Constraint
- Simulation Results
- Conclusions and Discussion
Chapter 82 - Probabilistic Tensor Analysis with Akaike and Bayesian Information Criteria
- Introduction
- Probabilistic Tensor Analysis
- Latent Tensor Model
- Probabilistic Tensor Analysis
- Dimension Reduction and Data Reconstruction
- Akaike and Bayesian Information Criteria for PTA
- Empirical Study
- Conclusion
- References
Chapter 83 - Decomposing EEG Data into Space-Time-Frequency Components Using Parallel Factor Analysis and Its Relation with Cerebral Blood Flow
- Introduction
- Theory
- Results
- Extracting Relevant Components from EEG
- Hemodynamic Response of Cerebral Blood Flow with Respect to EEG
- Discussion
- References
Chapter 84 - Flexible Component Analysis for Sparse, Smooth, Nonnegative Coding or Representation
- Introduction -- Problem Formulation
- Projected Gradient Local Least Squares Regularized Algorithm
- Flexible Component Analysis (FCA) -- Possible Extensions and Practical Implementations
- Nonnegative Matrix/Tensor Factorization
- Smooth Component Analysis (SmoCA)
- Multi-way Sparse Component Analysis (MSCA)
- Multi-layer Blind Identification
- Simulation Results
- Conclusions and Discussion
Chapter 85 - Appearance Models for Medical Volumes with Few Samples by Generalized 3D-PCA
- Introduction
- Background Knowledge of Multilinear Algebra
- Appearance Models Built by Generalized 3D-PCA
- Experiments
- Conclusion
Chapter 86 - Head Pose Estimation Based on Tensor Factorization
- Introduction
- Tensor Representation and Learning Algorithm
- Related Models for Tensor Decomposition
- The NMWF Algorithm
- Face Tensor Representation and Head Pose Estimation
- Simulations and Results
- Face Database
- TensorFaces Representation
- Head Pose Estimation
- Discussions and Conclusions
Chapter 87 - Kernel Maximum a Posteriori Classification with Error Bound Analysis
- Introduction
- Main Results
- Model Formulation
- Parameter Estimation
- Kernel Calculation
- Connection to Other Kernel Methods
- Separability Measures and Error Bounds
- Experiments
- Synthetic Data
- Benchmark Data
- Related Work
- Conclusion and Future Work
Chapter 88 - Comparison of Local Higher-Order Moment Kernel and Conventional Kernels in SVM for Texture Classification
- Introduction
- Local Moment and Local Moment Spectra
- Feature Extraction by Local Power Spectrum
- Local Higher-Order Moment Spectra (LHOMS)
- Support Vector Machine and Kernel Functions
- The LHOMS and LHOM Kernels
- LHOMS Kernel Derivation
- Equivalence of LHOMS and LHOM Kernels
- Texture Classification Experiments
- Experimental Conditions
- Sinusoidal Wave with Harmonic Components
- Fabric Texture
- Discussion
- Conclusion
Chapter 89 - Pattern Discovery for High-Dimensional Binary Datasets
- Introduction
- Dimension Reduction
- Singular Value Decomposition
- Semi-discrete Decomposition
- Non-negative Matrix Factorization
- Neural Network Based Boolean Factor Analysis
- Statistical Clustering Methods
- Experimental Results
- Conclusion
Chapter 90 - Expand-and-Reduce Algorithm of Particle Swarm Optimization
- Introduction
- Fundamental Version of PSO
- Expand-and-Reduce Algorithm
- Numerical Experiments
- Conclusions
Chapter 91 - Nonlinear Pattern Identification by Multi-layered GMDH-Type Neural Network Self-selecting Optimum Neural Network Architecture
- Introduction
- Heuristic Se1f-organization Method[1],[2]
- Revised GMDH-Type Neural Network Algorithm
- First Layer
- Second Layer
- Third and Successive Layers
- An Application to the Nonlinear Pattern Identification
- Identification Results Obtained Using the GMDH-Type Neural Network
- Identification Results Obtained Using the GMDH
- Identification Results Obtained Using the Conventional Neural Network
- Companion of the Identification Results
- Conclusion
- References
Chapter 92 - Coordinated Control of Reaching and Grasping During Prehension Movement
- Introduction
- Measurement Experiments
- Results
- Movement Time of Grasping and Reaching
- Grasping movements.
- Reaching movements.
- Relationship between grasping and reaching.
- Reaching without Grasping an Object
- Discussion
- Coordinated Mechanism between Reaching and Grasping
- Biological Plausibility of Computational Models
- Conclusion
Chapter 93 - Computer Simulation of Vestibuloocular Reflex Motor Learning Using a Realistic Cerebellar Cortical Neuronal Network Model
- Introduction
- Model
- Structure
- Description of Subsystems
- Description of Learning Rule
- Experimental Paradigms
- Results
- Simple and Complex Spike Firing Before Learning
- Simulation of VOR Motor Learning
- Discussion and Conclusion
Chapter 94 - Reflex Contributions to the Directional Tuning of Arm Stiffness
- Introduction
- Methods
- Apparatus
- Force Fields
- Protocol
- Results
- Endpoint Stiffness
- Electromyographic Activity
- Discussion
- References
Chapter 95 - Analysis of Variability of Human ReachingMovements Based on the Similarity Preservation of Arm Trajectories
- Introduction
- Experiment
- Measurement
- Simulated Trajectories with Noise
- Simulated Trajectories with the Uncertainty of Target Perception
- Analysis of the Similarity Preservation of Trajectories
- Results
- Discussion
Chapter 96 - Directional Properties of Human Hand Force Perception in the Maintenance of Arm Posture
- Introduction
- Hand Force Perception Experiment
- Experimental System
- Experimental Method
- Experimental Results
- Directional Properties of Human Hand Force Perception
- Human Force Perception Ellipse
- Relationship between Human Force Manipulability
- Conclusion
Chapter 97 - Computational Understanding and Modeling of Filling-In Process at the Blind Spot
- Introduction
- Evaluation Function for Filling-In
- Problems of Diffusion Equation for Filling-In Process
- New Functional with Curvature Terms
- Dynamics for Filling-In at the Blind Spot
- Neural Dynamics for Filling-In at the Blind Spot
- Numerical Simulations
- Summary
Chapter 98 - Biologically Motivated Face Selective Attention Model
- Introduction
- Biologically Motivated Selective Attention Model for Localizing Human Face
- Face Color Biased Selective Attention
- Ellipse Fitting Based on Symmetry Axes
- AAMLP for Face Localization
- Experimental Results
- Conclusion
- References
Chapter 99 - Multi-dimensional Histogram-Based Image Segmentation
- Introduction
- State-of-the-Art Figure-Background Segregation
- ``Trimap''-Based Methods
- Level-Set Methods
- Multi-dimensional Histogram-Based Image Segmentation
- Standard Level-Set Based Region Segmentation
- A Multi-dimensional Histogram-Based Level-Set Method for Image Segmentation
- Main Results
- Conclusion
Chapter 100 - A Framework for Multi-view Gender Classification
- Introduction
- Preprocessing
- Multi-scale Edge Enhancement
- Image Euclidean Distance (IMED)
- Layered Support Vector Machine
- Algorithm
- Complexity Analysis
- Experimental Results
- Experiment Setup
- Experiments on MSEE and IMED
- Experiments on LSVM
- Conclusions
Chapter 101 - Japanese Hand Sign Recognition System
- Introduction
- Hand Posture Recognition System
- Classifier Network
- Classifier Network for Hand Sign Recognition
- Hardware Configuration
- Simulation
- Recognition Rate and Circuit Size
- Conclusions
Chapter 102 - An Image Warping Method for Temporal Subtraction Images Employing Smoothing of Shift Vectors on MDCT Images
- Introduction
- Overall Scheme of the Temporal Subtraction Method
- Global Matching by Use of a 2-D Template Matching Technique
- Local Matching by Use of a 3-D Template Matching in VOIs
- Smoothing of Shift Vectors by Use of a 3-D Elastic Matching Technique
- Results
- Discussion and Conclusion
- References
Chapter 103 - Conflicting Visual and Proprioceptive Reflex Responses During Reaching Movements
- Introduction
- Methods
- Apparatus
- Mechanical Perturbations
- Visual Perturbations
- Joint Stiffness Estimation
- Electromyography
- Protocol
- Results
- Electromyography
- Contributions to Joint Stiffness
- Discussion
- References
Chapter 104 - An Involuntary Muscular Response Induced by Perceived Visual Errors in Hand Position
- Introduction
- Methods
- Apparatus
- Visual Perturbations
- Electromyography
- Experiment 1
- Experiment 2
- Results
- Experiment 1
- Experiment 2
- Discussion
- References
Chapter 105 - Independence of Perception and Action for Grasping Positions
- Introduction
- Measurement Experiment
- Measurement System
- Measurement Tasks
- Target Objects
- Experiment 1
- Experiment 2
- Result
- Experiment 1
- Experiment 2
- Discussion
- Independence of Perception and Action
- The Pinch Task and the Lift-Up Task as a Action Task
- Planning of Grasping Position
- Conclusion
Chapter 106 - Handwritten Character Distinction Method Inspired by Human Vision Mechanism
- Introduction
- Method of Fluctuation Extraction in Handwritten Characters Based on Vertical and Horizontal Orientation
- Texture Representation in Fourier Domain
- Extraction of a Fluctuation Feature Value Caused by Handwriting
- Verification Experiment
- Map of Feature Value E
- Summary
Chapter 107 - Recent Advances in the Neocognitron
- Introduction
- Outline of the Neocognitron
- Controlling the Blur in the Neocognitron
- Inhibitory Surround in the Connections to C-Cells
- Interpolating Vectors
- Incremental Learning of the Neocognitron
- Top-Down Signals into the Neocognitron
- How We Perceive Partly Occluded Patterns
- Recognition of Partly Occluded Patterns
- Restoration of Partly Occluded Patterns
Chapter 108 - Engineering-Approach Accelerates Computational Understanding of V1–V2 Neural Properties
- Introduction
- Standard Regularization Theory
- Long-Range Horizontal Connections
- Neural Evidence
- Computational Theory and Algorithm
- Simulation
- Filling-In at the Blind Spot
- Neural Evidence
- Computational Theory and Algorithm
- Simulation and Consideration
- Summary
Chapter 109 - Recent Studies Around the Neocognitron
- Introduction
- Summary of Neocognitron
- Network Architecture
- Learning Method
- Engineering Viewpoint Studies of the Neocognitron
- Comparison with ``Convolutional Net''
- Biological Viewpoint Studies of the Neocognitron
- The Property of Object Recognition Cells
- The Property of the Neocognitron Output Cells
- Other IT Cell Model
- Conclusion and Discussion
Chapter 110 - Toward Human Arm Attention and Recognition Using a Computer-Vision- and Neocognitron-Based Approach
- Introduction
- Estimation of Human Arm Posture Based on Stereo Vision
- Arm Model
- Method for Estimating Human Arm Posture
- Experiment
- Binocular Selective Attention Model Based on Neocognitron
- Neocognitron as an IT Model
- Binocular Selective Attention Model
- Future Works
Chapter 111 - Projection-Field-Type VLSI Convolutional Neural Networks Using Merged/Mixed Analog-Digital Approach
- Introduction
- Hierarchical CoNN Model for Object Detection
- CoNN LSI Processor Architecture and Related Algorithm
- 2D-MAC Calculation Schemes for CoNN LSI Processor Architecture
- Sorted Projection-Field Model
- LSI Processor Architecture for a Projection-Field Model
- Circuit Implementation Based on Merged/Mixed Analog-Digital Approach
- Proof-of-Concept LSIs
- Performance Estimation
- Conclusion
Chapter 112 - Optimality of Reaching Movements Based on Energetic Cost under the Influence of Signal-Dependent Noise
- Introduction
- Experimental Methods
- Results
- Discussion
- Conclusions
Chapter 113 - Influence of Neural Delay in Sensorimotor Systems on the Control Performance and Mechanism in Bicycle Riding
- Introduction
- Modeling
- Bicycle and Human Body
- Neural Network
- Reflex Motion in Bicycle Riding
- Single Input Network (Preliminary Experiment)
- Two Input Network (Bicycle Tilt and Its Changing Rate)
- Volitional Motion Relevant to Reflex Motion
- Tasks, Conditions, and Preparatory Reflex Motion Learning
- Results of the Learning
- Discussion
- Summary
Chapter 114 - Global Localization for the Mobile Robot Based on Natural Number Recognition in Corridor Environment
- Introduction
- Detection of the Door
- How to Detect the Door
- Local Goal Based Navigation
- Recognition of Room Number
- Extraction of Room Number Candidates
- Recognition of Room Number Using Multistage Rejection Method(MSRM)
- Experiments
- Conclusion
- References
Chapter 115 - A System Model for Real-Time Sensorimotor Processing in Brain
- Introduction
- Computational Approaches to the Brain Functions
- System Models for Sensorimotor Mechanism
- Gantt Chart for Brain Computation
- General Structure
- An Example: On-line Motor Planning of Reaching Movement
- Computation Flow in the Brain
- Computation and Variability of Neural Activities
- Information Processing through Inter-module Coupling
- Concluding Remarks
Chapter 116 - Perception of Two-Stroke Apparent Motion and Real Motion
- Introduction
- Perception of Two-Stroke Apparent Motion
- Phenomenon of Two-Stroke Apparent Motion
- Temporal Limits for the Perception of Two-Stroke Apparent Motion
- fMRI Study on Two-Stroke Apparent Motion
- Experimental Methods
- Experimental Results
- Discussions
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