LVQ学习矢量化算法源程序 This directory contains code implementing the Learning vector quantization network. Source code may be found in LVQ.CPP. Sample training data is found in LVQ1.PAT. Sample test data is found in LVQTEST1.TST and LVQTEST2.TST. The LVQ program accepts input consisting of vectors and calculates the LVQ network weights. If a test set is specified, the winning neuron (class) for each neuron is identified and the Euclidean distance between the pattern and each neuron is reported. Output is directed to the screen.
标签： implementing quantization directory Learning
上传时间： 2015-05-02
上传用户：hewenzhi
The objective of this projectis to design, model and simulate an autocorrelation generator circuit using 4-bit LFSR. the register and LFSR will used D flip-flop and some gates. By the autocorrelation concept, there should be 2 same length vectors, for calculating the autocorrelation , we have to design the register for storing the original vector and the shifter for make time delay.
标签： autocorrelation objective generator projectis
上传时间： 2015-08-17
上传用户：ikemada
关于 uC/OS-II 在 LPC210X 上移植的说明 1. 全部代码在 ADS1.2 中编译调试. 2. 您可以更改 RO BASE 为 0x0000 0000, 这样可以将代码写入 flash 中运行. 5. 全部代码采用 ARM 指令. 6. uC/OS-II 版本为 V2.52. 7. 当您暂停程序的时候, 如果定时器开着, 那么定时器并不会暂停,需要注意 8. vectors.S 文件中的 startup 段为程序入口. 9. 编译时下面的警告不必理会. Warning : C2871W: static OS_InitTaskStat declared but not used OS_CORE.C line 1108 10. 如果您想通过软件仿真,请将 PLL.C 中的第 51 行屏蔽, 怎样就可以看到任务逐个切换,最后将进入空闲任务. 11. 此次移植将许多 uC/OS-II 的功能函数都关闭了,请查看 OS_CFG.H 文件.
上传时间： 2013-12-25
上传用户：Divine
performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A *x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an m by n matrix
标签： alpha beta matrix-vector operations
上传时间： 2014-08-17
上传用户：qlpqlq
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) ％CUM2X Cross-covariance ％ y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag) ％ x,y - data vectors/matrices with identical dimensions ％ if x,y are matrices, rather than vectors, columns are ％ assumed to correspond to independent realizations, ％ overlap is set to 0, and samp_seg to the row dimension. ％ maxlag - maximum lag to be computed [default = 0] ％ samp_seg - samples per segment [default = data_length] ％ overlap - percentage overlap of segments [default = 0] ％ overlap is clipped to the allowed range of [0,99].
标签： cum2x y_cum Cross-covariance function
上传时间： 2015-09-08
上传用户：xieguodong1234
％CHECKBOUNDS Move the initial point within the (valid) bounds. ％ [X,LB,UB,X,FLAG] = CHECKBOUNDS(X0,LB,UB,nvars) ％ checks that the upper and lower ％ bounds are valid (LB <= UB) and the same length as X (pad with -inf/inf ％ if necessary) warn if too long. Also make LB and UB vectors if not ％ already. ％ Finally, inf in LB or -inf in UB throws an error.
标签： CHECKBOUNDS the initial bounds
上传时间： 2015-10-26
上传用户：caiiicc
This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen.
标签： code implementing directory algorithm
上传时间： 2014-01-15
上传用户：woshini123456
多项式曲线拟合 任意介数 Purpose - Least-squares curve fit of arbitrary order working in C++ Builder 2007 as a template class, using vector<FloatType> parameters. Added a method to handle some EMathError exceptions. If do NOT want to use this just call PolyFit2 directly. usage: Call PolyFit by something like this. CPolyFit<double> PolyFitObj double correlation_coefficiant = PolyFitObj.PolyFit(X, Y, A) where X and Y are vectors of doubles which must have the same size and A is a vector of doubles which must be the same size as the number of coefficients required. returns: The correlation coefficient or -1 on failure. produces: A vector (A) which holds the coefficients.
标签： Least-squares arbitrary Purpose Builder
上传时间： 2013-12-18
上传用户：宋桃子
k-meansy算法源代码。This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen.
标签： code implementing directory algorithm
上传时间： 2016-04-07
上传用户：shawvi
优化算法loqo的算法源代码。Purpose: solves quadratic programming problem for pattern recognition for support vectors
标签： programming recognition for quadratic
上传时间： 2016-04-09
上传用户：er1219
