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mp3readwrite

于 2010-11-15 发布 文件大小:2179KB
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  matlab files rock....kindly see in higher versions....

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  • bijiao
    阵元间隔为半波长的均匀分布16元线列阵,利用均匀加权常规波束。远场有5个互不相关的目标源发射信号,每个源相对基阵的方位分别为-40,-42,-5,30和33,且每个源信号到达基阵时的信噪比相等,均为10dB。分别对波束域和阵元域MUSIC算法进行比较。 (Array element spacing of half wavelength for the uniform distribution of 16 per linear array, using conventional beam evenly weighted. Far-field has five separate objectives of the source of emission signals, each source array of the relative position of-40,-42,-5,30 and 33, and each source signal to noise ratio at the time of Scientology Front equal, are 10dB. Separately on the beam element domain and the domain MUSIC algorithm for comparison.)
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    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...)
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