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squares

《squares》是一款由LEAPGameStudios制作并發行的益智類游戲。[1]

ClustanGraphics聚類分析工具。提供了11種聚類算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Li

ClustanGraphics聚類分析工具。提供了11種聚類算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean Proximity Centroid (UPGMC) Median (WPGMC) Increase in Sum of squares (Ward s Method) Sum of squares Flexible (ß space distortion parameter) Density (or k-linkage, density-seeking mode analysis)

標簽： ClustanGraphics Complete Neighbor Linkage

上傳時間： 2014-01-02

上傳用戶：003030
The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d

The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods. In higher dimensions, only a finite difference/linear algebra solution is provided, but it is fully vectorized and fully sparse in its approach. In 2-d and 3-d, if the gradients are inconsistent, then a least squares solution is generated

標簽： gradient function provided versions

上傳時間： 2016-11-07

上傳用戶：秦莞爾w
Mapack可用來做矩陣運算 Mapack is a .NET class library for basic linear algebra computations. It supports th

Mapack可用來做矩陣運算 Mapack is a .NET class library for basic linear algebra computations. It supports the following matrix operations and properties: Multiplication, Addition, Subtraction, Determinant, Norm1, Norm2, Frobenius Norm, Infinity Norm, Rank, Condition, Trace, Cholesky, LU, QR, Single Value decomposition, Least squares solver, Eigenproblem solver, Equation System solver. The algorithms were adapted from Mapack for COM, Lapack and the Java Matrix Package.

標簽： Mapack computations supports algebra

上傳時間： 2017-01-26

上傳用戶：tb_6877751
observable distribution grid are investigated. A distribution grid is observable if the state of th

observable distribution grid are investigated. A distribution grid is observable if the state of the grid can be fully determined. For the simulations, the modified 34-bus IEEE test feeder is used. The measurements needed for the state estimation are generated by the ladder iterative technique. Two methods for the state estimation are analyzed: Weighted Least squares and Extended Kalman Filter. Both estimators try to find the most probable state based on the available measurements. The result is that the Kalman filter mostly needs less iterations and calculation time. The disadvantage of the Kalman filter is that it needs some foreknowlegde about the state.

標簽： distribution observable grid investigated

上傳時間： 2014-12-08

上傳用戶：ls530720646
This is GPS in matlab calculatePseudoranges finds relative pseudoranges for all satellites listed

This is GPS in matlab calculatePseudoranges finds relative pseudoranges for all satellites listed in CHANNELLIST at the specified millisecond of the processed signal. The pseudoranges contain unknown receiver clock offset. It can be found by the least squares position search procedure.

標簽： calculatePseudoranges pseudoranges satellites relative

上傳時間： 2017-03-09

上傳用戶：時代電子小智
Basic function to locate and measure the positive peaks in a noisy data sets. Detects peaks by loo

Basic function to locate and measure the positive peaks in a noisy data sets. Detects peaks by looking for downward zero-crossings in the smoothed third derivative that exceed SlopeThreshold and peak amplitudes that exceed AmpThreshold. Determines, position, height, and approximate width of each peak by least-squares curve-fitting the log of top part of the peak with a parabola.

標簽： peaks function positive Detects

上傳時間： 2017-04-26

上傳用戶：彭玖華
Beamforming thesis describing Study of a various Beamforming Techniques And Implementation of the Co

Beamforming thesis describing Study of a various Beamforming Techniques And Implementation of the Constrained Least Mean squares (LMS) algorithm for Beamforming

標簽： Beamforming Implementation describing Techniques

上傳時間： 2013-12-25

上傳用戶：wuyuying
System identification with adaptive filter using full and partial-update Generalised-Sideband-Decomp

System identification with adaptive filter using full and partial-update Generalised-Sideband-Decomposition Least-Mean-squares

標簽： Generalised-Sideband-Decomp identification partial-update adaptive

上傳時間： 2017-09-13

上傳用戶：xcy122677
System identification with adaptive filter using full and partial-update Normalised-Least-Mean-Squar

System identification with adaptive filter using full and partial-update Normalised-Least-Mean-squares

標簽： Normalised-Least-Mean-Squar identification partial-update adaptive

上傳時間： 2017-09-13

上傳用戶：leixinzhuo
System identification with adaptive filter using full and partial-update Transform-Domain Least-Mean

System identification with adaptive filter using full and partial-update Transform-Domain Least-Mean-squares

標簽： Transform-Domain identification partial-update Least-Mean

上傳時間： 2014-01-12

上傳用戶：ztj182002