<acronym id="qkmou"></acronym> LVQ學習矢量化算法源程序 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.
標簽： implementing quantization directory Learning
上傳時間： 2015-05-02
上傳用戶：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.
標簽： autocorrelation objective generator projectis
上傳時間： 2015-08-17
上傳用戶：ikemada
關于 uC/OS-II 在 LPC210X 上移植的說明 1. 全部代碼在 ADS1.2 中編譯調試. 2. 您可以更改 RO BASE 為 0x0000 0000, 這樣可以將代碼寫入 flash 中運行. 5. 全部代碼采用 ARM 指令. 6. uC/OS-II 版本為 V2.52. 7. 當您暫停程序的時候, 如果定時器開著, 那么定時器并不會暫停,需要注意 8. vectors.S 文件中的 startup 段為程序入口. 9. 編譯時下面的警告不必理會. Warning : C2871W: static OS_InitTaskStat declared but not used OS_CORE.C line 1108 10. 如果您想通過軟件仿真,請將 PLL.C 中的第 51 行屏蔽, 怎樣就可以看到任務逐個切換,最后將進入空閑任務. 11. 此次移植將許多 uC/OS-II 的功能函數都關閉了,請查看 OS_CFG.H 文件.
上傳時間： 2013-12-25
上傳用戶：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
標簽： alpha beta matrix-vector operations
上傳時間： 2014-08-17
上傳用戶：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].
標簽： cum2x y_cum Cross-covariance function
上傳時間： 2015-09-08
上傳用戶：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.
標簽： CHECKBOUNDS the initial bounds
上傳時間： 2015-10-26
上傳用戶：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.
標簽： code implementing directory algorithm
上傳時間： 2014-01-15
上傳用戶：woshini123456
多項式曲線擬合 任意介數 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.
標簽： Least-squares arbitrary Purpose Builder
上傳時間： 2013-12-18
上傳用戶：宋桃子
k-meansy算法源代碼。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.
標簽： code implementing directory algorithm
上傳時間： 2016-04-07
上傳用戶：shawvi
優化算法loqo的算法源代碼。Purpose: solves quadratic programming problem for pattern recognition for support vectors
標簽： programming recognition for quadratic
上傳時間： 2016-04-09
上傳用戶：er1219
