Abstract: “In this paper, we developed a new State-Drop Fast Sequence Estimation (SDFSE) strategy for Trellis Coded Modulation (TCM) schemes for transmission in the Inter symbol Interference (ISI) environment. For the decoding of TCM signals in the presence of Additive White Gaussian Noise (AWGN), Maximum Likelihood Sequence Estimation (MLSE) has been considered as the optimum solution [13, 16, 17, 19]. However, for band-limited ISI channels in the presence of AWGN, the complexity of optimum MLSE increases as a function of the ISI channel memory length. This prohibits practical implementation of MLSE. Over the past decades, a spurious research took place in the development of reduced complexity suboptimum decoding strategies for TCM schemes. Reduced State Sequence Estimation (RSSE) is one such implementation which emphasizes on reduced computational complexity Likelihood sequence estimation by minimizing the ISI-code trellis states [23]. We provide a new suboptimum decoding strategy, a reduced co”

Keywords: Association rule mining, frequent item sets, Transaction Reduction, Content based image retrieval.