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PioncareMalt
Pioncare映射的全例子！从解法到时间历程以及映射的画法。(Pioncare Maps！)
- 2009-09-28 08:40:02下载
- 积分：1
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chazhi
插值算法程序，包含各种算法的例程。可以直接利用或者练习(algorithm program)
- 2010-01-19 15:26:50下载
- 积分：1
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dds
进行图像边缘检测的程序，学图像处理的会有很大帮助(Image edge detection procedure, learning image processing would be of considerable help)
- 2008-07-11 10:15:49下载
- 积分：1
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perceptron
说明： % 单层感知器 与、或、以及其他逻辑功能的实现
% 采用step逐步逐行运行方式，了解学习过程的细节
% 尝试重新定义程序中的T，观察感知器实现异或运算(T=1 0 1 0]的可能性。(% Implementation of Single Layer Perceptron and, or, and Other Logic Functions
% Use step-by-step operation to understand the details of the learning process
% Trying to redefine T in the program, observing the possibility of XOR operation (T = 1010) implemented by the perceptron.)
- 2020-06-20 03:40:01下载
- 积分：1
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DoubleFrequzeOneSource
矢量水听器倍频窄波束算法 原创 对传统的波束响应进行的改进算法(Vector Hydrophone octave narrow-beam algorithm originality of traditional beam response of the improved algorithm)
- 2020-11-08 16:29:48下载
- 积分：1
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8
说明： 《MATLAB 7.0编程基础基础》源程序，适合初学者使用，第8章(" MATLAB 7.0 programming foundation base" source, suitable for beginners, Chapter 8)
- 2011-06-13 17:44:22下载
- 积分：1
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GetHSVSimilarity
matlab语言编写写的求两个相同大小彩色图像HSV空间的巴氏距离(matlab language written request two HSV color image the same size space Bhattacharyya distance)
- 2014-08-17 14:13:00下载
- 积分：1
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gaosi
通过matlab语言编程，实现利用Gauss消去法求解线性方程组(Through matlab language programming, using the Gauss elimination method for solving linear equations)
- 2013-10-06 20:48:52下载
- 积分：1
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SIMULATED-ANNEALING-
这是一个关于商人visit许多城市，怎样走法才能使距离最短的例子，采样的了退火算法的经典案例(Traveling Salesman Problem (TSP) has been an interesting problem for a l
me in classical optimization techniques which are based on linear and nonlin
ogramming. TSP can be described as follows: Given a numberof cities to v
d their distances from all other cities know, an optimal travel route has to
und so that each city is visited one and only once with the least possible dista
aveled. This is a simple problem with handful of cities but becomes complica
the number increases.)
- 2013-12-15 03:26:30下载
- 积分：1
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SOM_NN_CODE
An important aspect of an ANN model is whether it needs
guidance in learning or not. Based on the way they learn, all
artificial neural networks can be divided into two learning
categories - supervised and unsupervised.
• In supervised learning, a desired output result for each input
vector is required when the network is trained. An ANN of the
supervised learning type, such as the multi-layer perceptron, uses
the target result to guide the formation of the neural parameters. It
is thus possible to make the neural network learn the behavior of
the process under study.
• In unsupervised learning, the training of the network is entirely
data-driven and no target results for the input data vectors are
provided. An ANN of the unsupervised learning type, such as the
self-organizing map, can be used for clustering the input data and
find features inherent to the problem.
- 2015-04-15 00:03:32下载
- 积分：1
