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定义浅层神经网络架构

定义浅层神经网络架构和算法

函数

networkCreate custom shallow neural network

示例和操作指南

自定义神经网络

Create Neural Network Object

Create and learn the basic components of a neural network object.

Configure Shallow Neural Network Inputs and Outputs

Learn how to manually configure the network before training using the configure function.

Understanding Shallow Network Data Structures

Learn how the format of input data structures affects the simulation of networks.

Edit Shallow Neural Network Properties

Customize network architecture using its properties and use and train the custom network.

历史和替代神经网络

Adaptive Neural Network Filters

Design an adaptive linear system that responds to changes in its environment as it is operating.

Perceptron Neural Networks

Learn the architecture, design, and training of perceptron networks for simple classification problems.

使用 2 输入感知器进行分类

2 输入硬限制神经元被训练为将 5 个输入向量分类为两个类别。

Outlier Input Vectors

A 2-input hard limit neuron is trained to classify 5 input vectors into two categories.

Normalized Perceptron Rule

A 2-input hard limit neuron is trained to classify 5 input vectors into two categories.

Linearly Non-separable Vectors

A 2-input hard limit neuron fails to properly classify 5 input vectors because they are linearly non-separable.

Radial Basis Neural Networks

Learn to design and use radial basis networks.

径向基逼近

此示例使用 NEWRB 函数创建一个径向基网络,该网络可逼近由一组数据点定义的函数。

Radial Basis Underlapping Neurons

A radial basis network is trained to respond to specific inputs with target outputs.

Radial Basis Overlapping Neurons

A radial basis network is trained to respond to specific inputs with target outputs.

GRNN Function Approximation

This example uses functions NEWGRNN and SIM.

PNN Classification

This example uses functions NEWPNN and SIM.

Probabilistic Neural Networks

Use probabilistic neural networks for classification problems.

Generalized Regression Neural Networks

Learn to design a generalized regression neural network (GRNN) for function approximation.

Learning Vector Quantization (LVQ) Neural Networks

Create and train a Learning Vector Quantization (LVQ) Neural Network.

学习向量量化

LVQ 网络训练为根据给定目标对输入向量进行分类。

Linear Neural Networks

Design a linear network that, when presented with a set of given input vectors, produces outputs of corresponding target vectors.

Linear Prediction Design

This example illustrates how to design a linear neuron to predict the next value in a time series given the last five values.

Adaptive Linear Prediction

This example shows how an adaptive linear layer can learn to predict the next value in a signal, given the current and last four values.

概念

Workflow for Neural Network Design

Learn the primary steps in a neural network design process.

Neuron Model

Learn about a single-input neuron, the fundamental building block for neural networks.

Neural Network Architectures

Learn architecture of single- and multi-layer networks.

Custom Neural Network Helper Functions

Use template functions to create custom functions that control algorithms to initialize, simulate, and train your networks.