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vind2sub--by-Chris
vind2sub by Chris
MATLAB s ind2sub function implemented to return a variable length vector (vector, matrix, utility)
- 2014-02-06 16:22:27下载
- 积分：1
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lfm
线性调频信号的时域波形、以及模糊函数图、距离分辨力、速度分辨力(Waveform, Ambiguity function, Distance resolution and Speed resolution of LFM)
- 2021-01-06 22:58:53下载
- 积分：1
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粗糙度
说明： 粗糙度计算程序，可以用来计算声学上的尖锐度，当然要先导入音频。。。。(Roughness calculation program, can be used to calculate the acoustic sharpness, of course, first to import audio....)
- 2020-06-04 17:06:35下载
- 积分：1
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control
某型三轴转台的控制程序，数据由试验得出。(A certain type of three-axis turntable control program, the data obtained by the test.)
- 2020-12-28 23:19:02下载
- 积分：1
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adaptiveFilter
说明： 空时自适应信号处理,滤波器设计资料,滤波器设计专著(spatial temporal filter)
- 2021-04-25 16:18:46下载
- 积分：1
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2011_inertial-navigation_second
2011年秋季 北京航空航天大学惯性导航原理第二次大作业(2011 inertial navigation the second homework of beihang university )
- 2013-11-11 15:35:27下载
- 积分：1
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sift_pitch
This MATLAB exercise designs and implements a pitch period detector based on detecting and tracking peaks in the autocorrelation of the LPC error signal during regions of voiced speech. The pitch detection procedure is called the SIFT (Simple Inverse Filtering Tracking) method. The SIFT pitch period detector uses a secondary autocorrelation peak in order to detect and correct pitch period detection errors due to effects such as pitch period doubling and related phenomena.
- 2014-02-14 18:26:43下载
- 积分：1
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QAM
利用matlab进行QAM的误码率仿真。利用ofdm技术。(Using matlab QAM BER simulation. Use ofdm technology.)
- 2014-01-28 18:35:23下载
- 积分：1
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超效率DEA
超效率DEA，可直接运行，但要注意输入量和输出量矩阵的形式，详细见内部说明文档(Super efficiency DEA)
- 2017-08-22 18:16:26下载
- 积分：1
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fecgm
独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE.
Jade performs `Source Separation in the following sense:
X is an n x T data matrix assumed modelled as X = A S + N where
o A is an unknown n x m matrix with full rank.
o S is a m x T data matrix (source signals) with the properties
a) for each t, the components of S(:,t) are statistically
independent
b) for each p, the S(p,:) is the realization of a zero-mean
`source signal .
c) At most one of these processes has a vanishing 4th-order
cumulant.
o N is a n x T matrix. It is a realization of a spatially white
Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance
sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE.
Jade performs `Source Separation in the following sense:
X is an n x T data matrix assumed modelled as X = A S+ N where
o A is an unknown n x m matrix with full rank.
o S is a m x T data matrix (source signals) with the properties
a) for each t, the components of S(:,t) are statistically
independent
b) for each p, the S(p,:) is the realization of a zero-mean
`source signal .
c) At most one of these processes has a vanishing 4th-order
cumulant.
o N is a n x T matrix. It is a realization of a spatially white
Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance
sigma. This is probably better than no modeling at all...)
- 2010-05-27 23:08:51下载
- 积分：1
