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Biomed
project, which shows the biomed-signal processing. Very simple
- 2011-01-03 02:30:01下载
- 积分：1
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PlotMohrsCircle
Matlab document consisting code of plotting the Mohr circles
- 2014-02-12 20:26:17下载
- 积分：1
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suijixulie
描述全部已知马尔科夫跳变系统的转移概率的一个生成模态(Describe all known markov jump to change the system transition probability of a generation mode)
- 2020-06-29 00:40:02下载
- 积分：1
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UseMatlabAdapterEqualingRLSandLMS
使用MATLAB工具利用RLS与LMS算法对信道进行均衡(using MATLAB tool use RLS and LMS algorithm in the channel for balance)
- 2007-05-30 11:43:03下载
- 积分：1
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GRID-CONNECTED-3PHASE-LOAD-MATLAB-SIMULATION
THIS SIMULATION INCLUDES GRID CONNECTED MATLAB SIMULATION.
- 2015-03-10 13:32:19下载
- 积分：1
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KarhunenLoeve
人脸识别领域的K-L变换（Eigenface）的matlab源码(KL transform the field of face recognition (Eigenface) of matlab source)
- 2007-08-13 16:18:00下载
- 积分：1
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Pdf_files_for_OFDM
OFDM Applications containing pdf files
- 2010-10-23 00:30:59下载
- 积分：1
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SCSToolboxV2
将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse
and compressible signals based on randomized dimensionality reduction. To recover a signal from its
compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or
frame that agrees with the measurements. A great many applications feature smooth or modulated signals
that are frequency sparse and can be modeled as a superposition of a small number of sinusoids.
Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the
sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery
performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery
algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a
signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)
- 2012-06-29 10:10:42下载
- 积分：1
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mfcc
求出语音mel倒谱系数的matlab代码，返回mfc(function mfc=mfcc(x) )
- 2014-01-23 20:39:47下载
- 积分：1
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GA
说明： 在考虑汽车零部件包装箱长、宽、高等三维尺寸的约束下，以配送中心为原点，分派多辆同一规格的货车到n个供应商处取货，最后回到配送中心。本章所构建的三维装载约束下的汽车零部件循环取货路径优化模型要解决的问题是确定循环取货路径，要求充分考虑汽车零部件在货车车厢中的三维装载位置，确保每个供应商处的零部件均能成功装载，尽可能使车辆装载率最大，且所有车辆的总行驶路径最短。(In considering the auto parts box length, width, higher dimensional size constraints to the distribution center as the origin, a multi-vehicle dispatch trucks to the same specifications of the pick n suppliers, and finally back to the distribution center. Auto Parts Pick cycle path constructed three-dimensional loading constraints under chapter optimization model to solve the problem is to determine the circulation pickup path requires full consideration in boxcars loaded in three-dimensional position of auto parts, to ensure that each vendor Parts can successfully loaded, as the vehicle maximum loading rate, and the total of all vehicles traveling the shortest route.)
- 2015-04-20 15:48:48下载
- 积分：1
