搜索资源列表
神经元模型
- 该程序模拟了神经元学习的过程.在学习过程中通过改变权值来慢慢接近教师信号.-the program to simulate the neurons learning process. In the process of learning by changing the value of the right of teachers to slowly close signal.
bp_proj
- BP网络是一种多层前馈神经网络，其神经元的变换函数是S型函数-BP is a multilayer feed-forward neural network, neurons in the transformation function is S-type function
自适用消噪源程序
- 由于线性神经元具自适应性，通过给出第一种信号，它能预测第二种信号-as neurons with linear adaptive, is the first signal, it forecast second signal
svm_train
- SVM simulator with neurons the code is in Csharp-SVM simulator with neurons the code is in Csharp..........
matlab
- 利用一个单隐层BP网络来逼近一个函数，在改程序中有21组数据。该网络的输入层和输出层的神经元个数均为一。-Using a single hidden layer BP network to approximate a function, in the reform process there were 21 sets of data. The network input layer and output layer are a number of neurons.
izh_single_neuron_tonic_RK
- It can be used in simulating izhikevich neurons
understanding_and_applying_machine_vision_0824789
- Perhaps because no important information is represented in absolute brightness values in the visual environment, the visual system has confined its processing almost exclusively to differences – spatial and temporal contrasts. Recording from ne
BP-neural-network
- BP神经网络，包括由大量的简单基本元件——神经元相互联接而成的自适应非线性动态系统。每个神经元的结构和功能比较简单，但大量神经元组合产生的系统行为却非常复杂。-BP neural network，By a large number of simple basic components- neurons interconnected by adaptive nonlinear dynamic systems. The structure and function of each neuron is
2-different-neurons(1)
- 对于两个不同神经元进行耦合后的体系进行模拟-Simulated for two different neurons coupled system
Hhhoopfild1o
- Hopfield 网——擅长于联想记忆与解迷路 实现H网联想记忆的关键，是使被记忆的模式样本对应网络能量函数的极小值。 设有M个N维记忆模式，通过对网络N个神经元之间连接权 wij 与N个输出阈值θjjj的设计，使的: 这M个记忆模式所对应的网络状态正好是网络能量函数的M个极小值。 比较困难，目前还没有一个适应任意形式的记忆模式的有效、通用的设计方法。 H网的算法 1）学习模式——决定权重 想要记忆 -Hopfield network- specializes in the associat
NEROPID1
- 控制领域中单神经元的实现，通过对外提供三个接口可实现个参数的直观访问与应用-Realization of single neurons in the control area by providing intuitive access and application of the three interfaces can be achieved parameters
Ncchhengxue
- 神经网络算法，单层输入，中间层100个神经元，一个输出神经元拟合sinx -Neural network algorithm, single input, the middle layer of 100 neurons, one output neuron fitting sinx
HTextRecognita
- 手写识别源码，具备fisher、、网格识别、神经元辨别的 -Handwriting recognition source code, have the fisher grid to identify neurons distinguish
izhikevichneurals
- 1000个神经元进行耦合，兴奋性神经元和抑制性神经元比例为四比一，绘出了它们的活动。-The 1000 neurons coupled excitatory neurons and inhibitory neurons in a ratio of four to one, draw their activities.
BP-network
- 掌握用BP网络解决实际预测问题的方法，包括数据规格化处理、训练样本和测试样本的组织，网络隐层层数和神经元个数的确定，以及传递函数和训练参数的确定等。-Mastered the method of BP network to solve practical prediction problems, including the normalized data processing, training samples and test samples of tissue, the number of
LIF_count
- Leaky intergration model，神经元里比较简单的模型。计算在一定时间内发放的次数-Leaky intergration model, a relatively simple model neurons. Calculating the number of payment within a certain time
Neural-network-algorithm
- 人工神经网络就是模拟人思维的第二种方式。这是一个非线性动力学系统，其特色在于信息的分布式存储和并行协同处理。虽然单个神经元的结构极其简单，功能有限，但大量神经元构成的网络系统所能实现的行为却是极其丰富多彩的。-Artificial neural network is the second way to simulate human thinking. This is a nonlinear dynamical system, which feature information distribut
osort-v3.0-code.tar
- 基于小波变换的神经元峰电位检测软件包，为什么要20个字-Neurons spike detection and sorting aaaaaaaaaaaaaaaaaaaaaaaaaaaaa
NN_Task1
- 建立一个bp神经网络解决异或问题：神经网络的结构采用2:2:1的结构，可以改变隐层神经元的个数。-Create a bp neural network to solve XOR problem: the structure of the neural network structure using 2:2:1, you can change the number of hidden layer neurons.
123
- 利用三层BP神经网络来完成非线性函数的逼近任务，其中隐层神经元个数为五个。-To complete the task of nonlinear function approximation by three layers of BP neural network, in which the number of hidden layer neurons into five.