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神经科学Matlab教程: Matlab科学计算导论 豆 0.0分
资源最后更新于 2020-07-25 14:08:44
作者:Pascal Wallisch
出版社:科学出版社
出版日期:2012-01
ISBN:9787030330567
文件格式: pdf
标签: 神经科学 matlab 编程 计算机 认知科学 科学 数学 psychology
简介· · · · · ·
《神经科学研究与进展•神经科学MATLAB教程:MATLAB科学计算导论(英文)(导读版)》内容简介:作为科学计算的数学软件,Matlab被广泛应用于几乎所有的神经科学和认知心理学实验室。《神经科学研究与进展•神经科学MATLAB教程:MATLAB科学计算导论(英文)(导读版)》介绍了Matlab的基础原理和基本程序设计、数据搜集与实验控制、数据分析与建模,帮助使用者解决各种计算问题。作者并非将Matlab单纯视为程序设计语言,而是将其作为解决神经科学实际问题的工具。
目录
Preface
Part I: Fundamentals
Introduction
Tutorial
Part II: Data Collection with Matlab
Visual Search and Pop Out
Attention
Psychophysics
Signal Detection Theory
Part III: Data Analysis with Matlab
Frequency Analysis Part I
Frequency Analysis Part II: Non-stationary Signals and Spectrograms
Wavelets
Convolution
Introduction to Phase Plane Analysis
Exploring the Fitzhugh-Nagumo Model
Neural Data Analysis: Encoding
Principal Components Analysis
Information Theory
Neural Decoding: Discrete variables
Neural Decoding: Continuous variables
Functional Magnetic Imaging
Part IV: Data Modeling with Matlab
Voltage-Gated Ion Channels
Models of a Single Neuron
Models of the Retina
Simplified Models of Spiking Neurons
Fitzhugh-Nagumo Model: Traveling Waves
Decision Theory
Markov Model
Modeling Spike Trains as a Poisson Process
Synaptic Transmission
Neural Networks: Unsupervised learning
Neural Network: Supervised Learning
Appendices
Appendix 1: Thinking in Matlab
Appendix 2: Linear Algebra Review
Part I: Fundamentals
Introduction
Tutorial
Part II: Data Collection with Matlab
Visual Search and Pop Out
Attention
Psychophysics
Signal Detection Theory
Part III: Data Analysis with Matlab
Frequency Analysis Part I
Frequency Analysis Part II: Non-stationary Signals and Spectrograms
Wavelets
Convolution
Introduction to Phase Plane Analysis
Exploring the Fitzhugh-Nagumo Model
Neural Data Analysis: Encoding
Principal Components Analysis
Information Theory
Neural Decoding: Discrete variables
Neural Decoding: Continuous variables
Functional Magnetic Imaging
Part IV: Data Modeling with Matlab
Voltage-Gated Ion Channels
Models of a Single Neuron
Models of the Retina
Simplified Models of Spiking Neurons
Fitzhugh-Nagumo Model: Traveling Waves
Decision Theory
Markov Model
Modeling Spike Trains as a Poisson Process
Synaptic Transmission
Neural Networks: Unsupervised learning
Neural Network: Supervised Learning
Appendices
Appendix 1: Thinking in Matlab
Appendix 2: Linear Algebra Review