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fast-method
机械最优化设计中，无约束条件的最速下降法(Mechanical design optimization, unconstrained conditions steepest descent method)
- 2014-11-27 15:40:11下载
- 积分：1
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Trafficflowforecasting
车流量预测 ，采用MATLAB进行编写。(Traffic flow forecasting, using MATLAB to write.)
- 2010-01-10 16:18:40下载
- 积分：1
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BPSKber
关于BPSK的误码率的MATLAB仿真程序。是在高斯信道（AWGN)下的仿真，能够生成图像形式。(BPSK bit error rate on the MATLAB simulation program. In the Gaussian channel (AWGN) under the simulation, can generate the image forms.)
- 2010-05-22 14:58:28下载
- 积分：1
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Histogram_irregular
This program create histogram for irregular objects like leaf, map, shape of tongue etc.
- 2011-09-17 11:44:04下载
- 积分：1
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qpsk_demod_ZiBian
考虑载波的qpsk信号在瑞利信道上的仿真(consider Carrier qpsk Rayleigh channel signal simulation)
- 2006-11-06 08:27:23下载
- 积分：1
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aci
feature extraction matlab code
- 2011-09-30 16:13:05下载
- 积分：1
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666616psk
RLS算法，用matlab实现，用自适应算法来实现均衡，程序正确(RLS algorithm, using matlab to achieve, with an adaptive algorithm to achieve a balanced and correct procedures)
- 2012-09-05 21:51:26下载
- 积分：1
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cluster-validity-measure-and-its-applicatio
cluster validity measure and its applicatio
- 2014-02-20 10:09:25下载
- 积分：1
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Pedometer
自己编写的基于卡尔曼滤波的利用加速度传感器的计步器，测试数据是传感器放在腰部和手臂。(A kF-based pedometer using accelerator.)
- 2013-05-30 15:17:04下载
- 积分：1
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Matlab-Noise-Reduction
说明： LMS (Least Mean Squares): most basic canonical ANC algo
FxLMS (Filtered eXtended Least Mean Squares): adds an additional learned filter for the secondary path signal - signal from cancellation speakers to users ears - to account for phase problems and audio coloration added during practical noise cancellation applications
NLMS (Normalized Least Mean Squares): adds simple adaptively updated learning rate on top of LMS to speed convergence.
FxNLMS (Normalized Filtered eXtended Least Mean Squares): combines FxLMS and NLMS
FuNLMS (Filtered-u Last Mean Squares): adds an additional active LMS filter to FxNLMS to cancel out noise bleeding from the cancellation speaker to the error mic. Fairly robust but convergence not gaurunteed!
- 2019-01-23 00:18:22下载
- 积分：1
