viterbi decoding Archives - GaussianWaves https://www.gaussianwaves.com/tag/viterbi-decoding/ Signal Processing for Communication Systems Fri, 25 Aug 2023 11:03:53 +0000 en-US hourly 1 https://wordpress.org/?v=6.5.3 https://i0.wp.com/www.gaussianwaves.com/gaussianwaves/wp-content/uploads/2016/02/cropped-gaussianwaves_logo_120_120.png?fit=32%2C32&ssl=1 viterbi decoding Archives - GaussianWaves https://www.gaussianwaves.com/tag/viterbi-decoding/ 32 32 163393712 Convolutional Codes – sliding window and shift register https://www.gaussianwaves.com/2023/08/convolutional-codes-sliding-window-and-shift-register/ https://www.gaussianwaves.com/2023/08/convolutional-codes-sliding-window-and-shift-register/#respond Fri, 25 Aug 2023 13:00:00 +0000 https://www.gaussianwaves.com/?p=37839 Key focus : Convolutional codes: Error-correcting codes effective in noisy channels and burst error correction. Know about sliding window & shift registers and how they are used in a convolutional encoder. Linear block codes Linear block codes, like Hamming codes, are mainly employed in hard decision decoding, utilizing the inherent algebraic structure of the code ... Read more

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Hidden Markov Models (HMM) – Simplified !!! https://www.gaussianwaves.com/2020/03/hidden-markov-models-hmm-simplified/ https://www.gaussianwaves.com/2020/03/hidden-markov-models-hmm-simplified/#comments Tue, 17 Mar 2020 05:08:35 +0000 https://www.gaussianwaves.com/?p=22270 Markov chains are useful in computing the probability of events that are observable. However, in many real world applications, the events that we are interested in are usually hidden, that is we don’t observe them directly. These hidden events need to be inferred. For example, given a sentence in a natural language we only observe the ... Read more

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Markov Chains – Simplified !! https://www.gaussianwaves.com/2020/03/markov-chains-simplified/ https://www.gaussianwaves.com/2020/03/markov-chains-simplified/#respond Fri, 06 Mar 2020 07:11:37 +0000 https://www.gaussianwaves.com/?p=22215 Key focus: Markov chains are a probabilistic models that describe a sequence of observations whose occurrence are statistically dependent only on the previous ones. ● Time-series data like speech, stock price movements.● Words in a sentence.● Base pairs on the rung of a DNA ladder. States and transitions Assume that we want to model the ... Read more

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