搜索资源列表
Perceptron_Function
- 感知器算法，利用C语言实现。利用梯度下降法进行迭代求解。-Perception algorithm, using C language, that is, we usually write operations, to share with you. . . .
perceptron
- 基于VC++实现感知器模式识别，并用OPENGL显示分类结果-The perceptron Pattern Recognition based VC++ OPENGL classification results
Perceptron-Approach-with-matlab-
- 用matlab软件编写感知器算法，实现对样本的分类，样本点为X1(0，0)，X2(0，-1)，X3(-1，0)，X4(-1，-1) -Perceptron Approach with matlab
artifical-nerual-network
- 人工神经网络感知器，利用样本点训练网络并绘出得到的分类线-artifical nerual network
classifer
- 二分类问题采用包括逻辑回归、最小二乘法、感知器算法（按下space不断迭代）、svm线性分类，另外还有高斯分线性分类（待完善），针对平面上两类点进行分类-Second classification using logistic regression, the method of least squares, perception algorithm (Press space iteratively) svm linear classification, in addition to the Ga
C
- 模式识别中的感知器算法，是基于三维的。算法简单易懂。-Perception algorithm in pattern recognition, which is based on three-dimensional.
Perceptron-Algorithm
- 模式识别是对样本进行聚类，感知器算法是通过迭代计算修正权向量，使样本满足条件，从而实现分类。本程序对感知器算法进行了改进，当权向量不满足时，立即退出此轮计算，进入下一轮迭代，从而减少了计算次数。程序对代码有详细注释，对样本的个数和维数自动判别。-Pattern recognition, clustering samples, perception algorithm is iterative correction weight vector samples meet the conditions
gzq
- 感知器算法，可以实现线性分类，中间步骤很详细，明确表示算法过程-Perception algorithm can achieve linear classification, an intermediate step in great detail, expressly algorithm process
perception_two
- 对两类的问题采用感知器算法进行分类，该方法能够有效的计算出代价函数-Two types of problems with the perception algorithm for classification, this method can effectively calculate the cost function.
Sensor-network
- 计算双输入单输出的感知器网络的网络权值。参考输入输出为： x1(1)=1 x2(1)=1 d(1)=1； x1(2)=-0.5 x2(2)=-1 d(2)=-1； x1(3)=3 x2(3)=1 d(3)=1； x1(4)=-2 x2(4)=-1 d(4)=-1；-Calculation of the dual-input single-output perceptron network weights. Reference input and output: &
pattern-recognizer
- 用matlab软件编写感知器算法，实现对样本的分类，样本点为X1(0，0)，X2(0，-1)，X3(-1，0)，X4(-1，-1) X1,X2属于第一类，X3、X4属于第二类；（编程） X1、X4属于第一类，X2，X3属于第二类；（计算）-Perceptron Algorithm matlab software, to achieve the classification of samples, sample points X1 (0,0), X2 (0,-1), X3 (-1,0
perceptron
- 模式识别-梯度下降法特例的感知器算法的Matlab实现，实现两类线性分类。-Pattern-Recognition，The perceptron algorithm based on MATLAB
ganzhiqi
- 感知器法的matlab实现，程序已经实现，源程序和结果图像放在word中，通知也包含可直接运行的matlab程序。-The perceptron method matlab to achieve, the program has been achieved, the source code and the resulting image is placed in the word, the notice also contains matlab program can be run direct
moshishibie
- C# 模式识别作业 最大最小距离算法（可以实现鼠标收入） 感知器-C# pattern recognition operating the largest minimum distance the algorithm (mouse income) sensor
code
- 三道题，包括1：用多层感知器（MLP）神经网络误差反向传播（BP）算法实现异或问题:2：用奇阶互补法设计两带滤波器组(高、低通互补)，进而实现四带滤波器组 3：估计其功率谱-Three questions, including: 1 using multilayer perceptron ( MLP ) neural network and error back propagation ( BP ) algorithm to realize the XOR problem: 2: the odd
1
- 双输入单输出系统 x1(1)=1 x2(1)=1 d(1)=1 x1(2)=-0.5 x2(1)=-1 d(1)=-1 x1(3)=3 x2(1)=1 d(1)=1 x1(4)=-2 x2(1)=-1 d(1)=-1 建立一个感知器网络，实现上述样本的分类，计算出相应的网络权值矩阵W-Dual-input single-output system x1 (1) = 1 x2 (1) = 1 d (1) = 1 x1 (2) =-0.5 x2 (1) =-1 d (1) =-
ANN_bp
- 用于训练多层感知器的神经网络BP算法C++源程序，有较为详细的注释。-For the training of Multilayer Perceptron Neural Network the BP algorithm C++ source, more detailed notes.
Neural-network-classified
- 神经网络系统，关于感知器程序，对如下输入、输出样本进行分类，输入样本如下： 所对应的输出的10组二元目标矢量为： -Neural network system perceptron procedures classified as input and output samples and input samples as follows: corresponding to the output of the 10 groups of the binary target vector:
12
- 关于人工神经网络中感知器的matlab算法-The matlab algorithm is on artificial neural network sensor
perception-algorithm
- 模式识别中的经典算法，感知器算法在matlab中的编程实现-The classic pattern recognition algorithms, perception algorithm in matlab programming