This project implements a robust Part-of-Speech (POS) tagger from scratch using a Hidden Markov Model (HMM) framework. It explores and compares three n-gram models (Unigram, Bigram, and Trigram) to ...

Sequence-based protein function and structure prediction depends crucially on sequence-search sensitivity and accuracy of the resulting sequence alignments. We present an open-source, general-purpose ...

This project parses a small discrete HMM from a text file, reads an observation sequence, runs the Viterbi dynamic programming algorithm (using log-probabilities), and prints the most likely ...

Abstract: Viterbi algorithm is a dynamic programming algorithm used to find out the most likely word uttered by the unknown speech signal. In Viterbi algorithm, the observation probabilities are ...

Abstract: Despite available prior knowledge, existing pulse deinterleaving algorithms for multifunctional radars (MFRs) suffer from limited robustness and high computational complexity. To address ...