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Probability And Stochastic Processes - A Friendly Introduction For Electrical And Computer Engineers (Matlab Code 22S) Roy D Yates
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This book provides an overview and introduction to signal detection and
estimation. The book contains numerous examples solved in detail. Since some
material on signal detection could be very complex and require a lot of background
in engineeri
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solution of probability, random variables and stochastic processes
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Adaptive Filtering Primer with MATLAB® clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic process
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一种HMM可以呈现为最简单的动态贝叶斯网络。隐马尔可夫模型背后的数学是由LEBaum和他的同事开发的。它与早期由RuslanL.Stratonovich提出的最优非线性滤波问题息息相关,他是第一个提出前后过程这个概念的。
在简单的马尔可夫模型(如马尔可夫链),所述状态是直接可见的观察者,因此状态转移概率是唯一的参数。在隐马尔可夫模型中,状态是不直接可见的,但输出依赖于该状态下,是可见的。每个状态通过可能的输出记号有了可能的概率分布。因此,通过一个HMM产生标记序列提供了有关状态的一些序
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understanding of the fundamental concepts incorporated in stochastic processes, estimation
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