Viterbi Maximum Liklihood Decoding

Last night I was following up on a hunch that the Viterbi Maximum Liklihood Decoding algorithm could have application for spell checking. I remembered this algorithm from a class I took at Carnegie Mellon called Digital Communications. I went back to the course book, and started reviewing the matter. I hadn't remembered this course book as standing out from others, but now I can really appreciate how well written it is. It has very clear treatment of the subject matter with well broken-out examples, that build throughout the topic. Sklar is a great writer, and he clearly loves the subject matter. I like his pithy conclusions at the end of each chapter. He has a flair for understatement:

"In the last decade, coding emphasis has been in the area of convolutional codes since in almost every application, convolutional codes outperform block codes for the same implementation complexity of the encoded-decoder. For satellite communications channels, forward error correction techniques can easily reduce the required SNR for specified error performance by 5 to 6dB. This coding gain can translated directly into an equivalent reduction in required satellite effective radiated power (EIRP), which consequently reduced satellite weight and cost."

After reviewing the Viterbi algorithm, I was curious about who this Viterbi guy was, anway. I'd also seen a chart in the Sklar book, attributed to the "Linkabit" corporation. Turns out Viterbi founded Linkabit, then later Qualcomm, an eventually donated $50 million to USC where the Viterbi school of engineering bears his name. Interesting story.

Oh, and it turns out the Viterbi algorithm does have applications to spell checking.