搜索资源列表
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多种人工神经网络：MATLAB源程序用于训练测试-variety of artificial neural networks : MATLAB source for training tests
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这是一段利用MATLAB中gatool快速实现训练神经网络的遗传算法程序-It was a quick realization of the use of MATLAB, gatool training neural networks, genetic algorithms program
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该程序包包含三个函数，一个用于建立BP神经网络，一个用于训练该网络，最后一个用于测试样本。-The package contains three functions, one for the establishment of BP neural networks, one for training the network, the last one for the test samples.
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模糊神经网络，自己编的，解决神经网络全局收敛问题，训练速度快。-Fuzzy neural networks, own, and to resolve the issue of global convergence of neural network training speed.
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用遗传算法优化bp神经网络的权值，并训练以及验证网络-Bp by using genetic algorithms to optimize the weights of neural networks, and network training and validation
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CNN Class, ver 0.72.
Change log:
Ver 0.72:
Sample GUI added, demonstrating use of convolutional network for handwriten digits recognition.
Training runs 20 faster.
Ver 0.71:
Bug fix: training was stoped after 1 epoch.
Ver 0.70:
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RBF. Training radial basis neural networks with the extend Kalman filter
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Image Compression using Artificial Neural Networks
This code is developed in MATLAB 6.5 and can used in Windows platform. Program contain all necessary files. For training the network use Train.m and Codec.m compress images by trained network.
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这是本人编写的matlab的GUI程序，可以实现交互式的界面。里面的程序是bp神经网络的应用，另一个回归分析的程序还没有写。可以实现的功能是利用神经网络，然后上传数据，根据数据训练网络，然后可以输入部分数据，验证网络。-This is my GUI program written in matlab, you can achieve interactive interface. Bp inside the program is the application of neural networks
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支持向量机和BP神经网络虽然都可以用来做非线性回归，但它们所基于的理论基础不同，回归的机理也不相同。支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。为了验证这种观点，本文编写了支持向量机非线性回归的通用Matlab程序和基于神经网络工具箱的BP神经网络仿真模块，仿真结果证实，支持向量机做非线性回归不仅泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。-SVM and BP neural networks, although non-linear regr
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The early detection of arrhythmia is very important
for the cardiac patients. This done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different typ
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神经网络matlab训练网络和测试网络程序-Matlab neural network training networks and network testing procedures
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a good document about Neural networks and CHARACTER RECOGNITION Handwritten character Recognition: Training a Simple NN for classification using MATLAB
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自适应神经网络图书馆（Matlab的5.3.1或更高版本）是实现多个自适应神经网络具有不同的自适应算法块的集合。
它主要分布于2001年6月 - 7月詹皮耶罗坎帕（西弗吉尼亚大学）和马里奥·卢卡Fravolini（佩鲁贾大学）。后来改善部分由美国航天局资助NCC5-685支持。
有迹象表明，实施基本上这些种神经网络的块：
自适应线性网络（ADALINE）
多层感知层网络
广义径向基函数网络
动力单元结构（DCS）网络的高斯或圆锥形基函数
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通过反复训练模板能有较高的识别率，zFzySva参数现代信号处理中谱估计在matlab中的使用，对于初学者具有参考意义，结合PCA的尺度不变特征变换(SIFT)算法，EyFKrQV条件包括最小二乘法、SVM、神经网络、1_k近邻法,具有丰富的参数选项。- Through repeated training zFzySvalate have higher recognition rate, zFzySva parameter Modern signal processing used in th
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matlab程序，使用神经网络估算信号频率，附训练及测试数据(The matlab program uses neural networks to estimate the frequency of signals, along with training and test data)
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BP神经网络和lvq神经网络的MATLAB程序，程序中包含有网络的识别效果图。(BP neural network and LVQ neural network training and pattern recognition)
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Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. The entire training process BP neural network.
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神经网络的简单数据训练的程序，通过训练数据生成符合数据的神经网路(A simple data training program for neural networks that generates neural networks that match data through training data.)
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