Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Trellis source codes consist of a finite-state machine decoder and a trellis search algorithm, such as the Viterbi algorithm, as the encoder. The encoder experiments with a local copy of the decoder and determines the best channel path map in the sense that it will yield the smallest average distortion beten the source sequence and the reproduction sequence given the codebook.   present a coding system and a design algorithm for predictive trellis coding. Results obtained via simulation are compared for trellis and predictive trellis codes designed for first-order autoregressive sources with Gaussian and Laplacian innovations and for sampled speech. On a random source which models speech, simulation results of the predictive and nonpredictive trellis codes designed by the generalized Lloyd algorithm and those obtained by other researchers are compared. Issues related to computational complexity, the effects of initial codebook selection, training sequence segmentation, search length, channel errors, and algorithm convergence are addressed.
['Ender Ayanoglu', 'Robert M. Gray']
I am writing a research paper on a idea The Design of Predictive Trellis Waveform Coders Using the Generalized Lloyd Algorithm
[{"from": "human", "value": "I am writing a research paper on a idea The Design of Predictive Trellis Waveform Coders Using the Generalized Lloyd Algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Trellis source codes consist of a finite-state machine decoder and a trellis search algorithm, such as the Viterbi algorithm, as the encoder. The encoder experiments with a local copy of the decoder and determines the best channel path map in the sense that it will yield the smallest average distortion beten the source sequence and the reproduction sequence given the codebook.   present a coding system and a design algorithm for predictive trellis coding. Results obtained via simulation are compared for trellis and predictive trellis codes designed for first-order autoregressive sources with Gaussian and Laplacian innovations and for sampled speech. On a random source which models speech, simulation results of the predictive and nonpredictive trellis codes designed by the generalized Lloyd algorithm and those obtained by other researchers are compared. Issues related to computational complexity, the effects of initial codebook selection, training sequence segmentation, search length, channel errors, and algorithm convergence are addressed."}]