hmm

, 'OverlapLength', overlapLength); % Calculate likelihood for each trained HMM likelihoods = zeros(1, numClasses); for i = 1:numClasses likelihoods(i) = hmmdecode(testFeatures, hmmModels{i}.Trans, hmmModels{i}.Mu, hmmModels{i}.Sigma); end % Identify the c

bridging human language and machine understanding. Whether as a standalone tool or as part of hybrid systems, HMMs’ legacy endures, exemplifying the enduring strength of statistical approaches in complex pattern recognition