A method for minimizing errors in a modulated signal transmitted over a transmission medium. The method is applied to the entire data block, thereby incorporating information about the parities of each row of data to fix and correct the errors in the row. Thereafter ISI removal is applied on a row by row basis, with such corrections being applied via soft decision coding. In particular, the data samples are first collected in a data block (or FEC block). A soft decision buffer is thereafter created by taking each sample involved. An FEC word is created by processing down each row of the soft decision buffer and creating a binary stream out of the sign bits for each table entry. This creates an estimate of the word by thresholding it around the zero level. A syndrome is generated via a comparison of the parity bits for each FEC word. The syndrome provides the most likely bit error positions, represented by an offset into the FEC word. The error positions map back into the array of soft decision buffer entries and the absolute value entries are summed for each corresponding position. This produces sets of numbers and the set with the smallest value is used to indicate the error pattern. The bits believed to be in error are flipped in the FEC word. ISI removal is applied to the soft decision buffer on a row-by-row basis (excluding the first row) to create an intermediate data frame, referred to as the Rx Frame. Upon completion, the process is repeated in the other direction for all of the rows except the last row, on a row-by-row basis. Upon completion, the data block errors will be minimized and the received block should match the transmitted block. The process therefore provides minimal data block errors, but at the same time uses less processing resources.