Define Shallow Neural Network Architectures

Define shallow neural network architectures and algorithms

Functions

`网络`	Create custom shallow neural network

示例以及如何

Custom Neural Networks

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 theconfigurefunction.
Understanding Shallow Network Data Structures
了解输入数据结构的格式如何影响网络的仿真。
编辑浅神经网络属性
使用其propertie定制网络体系结构s and use and train the custom network.

Historical and Alternative Neural Networks

自适应神经网络过滤器
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.
Classification with a Two-Input Perceptron
A two-input hard limit neuron is trained to classify four input vectors into two categories.
离群值输入向量
对2输入硬限制神经元进行了训练，将5个输入向量分为两类。
Normalized Perceptron Rule
对2输入硬限制神经元进行了训练，将5个输入向量分为两类。
线性不可分割的向量
A 2-input hard limit neuron fails to properly classify 5 input vectors because they are linearly non-separable.
径向基础神经网络
Learn to design and use radial basis networks.
Radial Basis Approximation
This example uses the NEWRB function to create a radial basis network that approximates a function defined by a set of data points.
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.
广义回归神经网络
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.
Learning Vector Quantization
An LVQ network is trained to classify input vectors according to given targets.
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
此示例显示了自适应线性层如何学会预测信号中的下一个值，给定当前和最后四个值。

Concepts

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.