LDPC碼譯碼相關(guān)文獻(xiàn) Bounds on the maximum likelihood decoding error probability of low density parity check codes
標(biāo)簽： probability likelihood decoding maximum
上傳時(shí)間： 2015-11-25
上傳用戶：wendy15
A general decision rule for stochastic blind Maximum-Likelihood OSTBC detection is derived.
標(biāo)簽： Maximum-Likelihood stochastic detection decision
上傳時(shí)間： 2013-12-04
上傳用戶：xcy122677
A stack-based sequential depth-first decoder that returns Maximum-Likelihood solutions to spherical LAST coded MIMO system-type problems
標(biāo)簽： Maximum-Likelihood stack-based depth-first sequential
上傳時(shí)間： 2013-12-20
上傳用戶：hebmuljb
he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.
標(biāo)簽： equivalent likelihood algorithm Sejnowski
上傳時(shí)間： 2016-09-17
上傳用戶：Altman
Maximum Likelihood Methods in Radar Array Signal Processing
標(biāo)簽： Likelihood Processing Maximum Methods
上傳時(shí)間： 2013-12-29
上傳用戶：dave520l
This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
標(biāo)簽： performance likelihood decision feedback
上傳時(shí)間： 2013-11-25
上傳用戶：1079836864
Implements Maximum likelihood estimation of beta and other parameters for model of stock portfolio vs. index using kalman filter
標(biāo)簽： Implements likelihood estimation parameters
上傳時(shí)間： 2013-12-28
上傳用戶：zhangzhenyu
A one-dimensional calibration object consists of three or more collinear points with known relative positions. It is generally believed that a camera can be calibrated only when a 1D calibration object is in planar motion or rotates around a ¯ xed point. In this paper, it is proved that when a multi-camera is observing a 1D object undergoing general rigid motions synchronously, the camera set can be linearly calibrated. A linear algorithm for the camera set calibration is proposed，and then the linear estimation is further re¯ ned using the maximum likelihood criteria. The simulated and real image experiments show that the proposed algorithm is valid and robust.
標(biāo)簽： one-dimensional calibration collinear consists
上傳時(shí)間： 2014-01-12
上傳用戶：璇珠官人
Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique.
標(biāo)簽： performance equalizers Adaptive several
上傳時(shí)間： 2016-02-16
上傳用戶：yan2267246
自己編的matlab程序。用于模式識(shí)別中特征的提取。是特征提取中的Sequential Forward Selection方法，簡(jiǎn)稱sfs.它可以結(jié)合Maximum-Likelihood-Classifier分類器進(jìn)行使用。
標(biāo)簽： Sequential Selection Forward matlab
上傳時(shí)間： 2016-04-02
上傳用戶：ma1301115706
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