this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) fi
this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) fi...
hidden技術資料
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?? hidden全部資料 (42個)
CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001 Matlab toolbox for max. aposteriori e
CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001 Matlab toolbox for max. aposteriori e...
madCollection 2.5.2.6 full source This is not your every day VCL component collection. You won t se
madCollection 2.5.2.6 full source This is not your every day VCL component collection. You won t se...
Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right
Hidden_Markov_model_for_automatic_speech_recognition This code implements in C++ a basic left-right...
If you have programming experience and a familiarity with C--the dominant language in embedded syste
If you have programming experience and a familiarity with C--the dominant language in embedded syste...
本人編寫的incremental 隨機神經元網絡算法
本人編寫的incremental 隨機神經元網絡算法，該算法最大的特點是可以保證approximation特性，而且速度快效果不錯，可以作為學術上的比較和分析。目前只適合benchmark的regre...
Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that s
Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that s...
Batch version of the back-propagation algorithm. ％ Given a set of corresponding input-output pairs
Batch version of the back-propagation algorithm. ％ Given a set of corresponding input-output pairs ...
％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is p
％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is p...
Train a two layer neural network with a recursive prediction error ％ algorithm ("recursive Gauss-Ne
Train a two layer neural network with a recursive prediction error ％ algorithm ("recursive Gauss-Ne...