Main Idea: This paper claims that a Recurrent Neural Network can learn from data to decode noisy signal over Additive White Gaussian Noise (AWGN) Channel as good as Viterbi and BCJR algorithm.

本文简明讲述GMM-HMM在语音识别上的原理，建模和测试过程。 ANS：一个有隐节点（unobservable）和可见节点（visible）的马尔科夫过程（见详解）。 隐节点表示状态，可见节点表示我们听到的语音或者看到的时序信号。 最开始时，我们指定这个HMM的结构，训练HMM ...

A complete C++ implementation of the Python hmmlearn library, featuring modern C++17, Eigen for linear algebra, and comprehensive HMM algorithms. hmm_c++/ ├── include/ # Header files │ ├── types.hpp # ...

Abstract: This paper presents algorithms for the parallelization of inference in hidden Markov models (HMMs). In particular, we propose a parallel forward-backward type of filtering and smoothing ...

Abstract: The use of Hidden Markov Models for radar frequency track detection is studied in this paper. In particular, we focus on periodic signals, and propose a new algorithm that incorporates ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. As a supervised machine learning algorithm, conditional random fields are mainly used ...

The ventral visual stream (VVS) is a fundamental pathway involved in visual object identification and recognition. In this work, we present a hypothesis of a sequence of computations performed by the ...