Abstract: A method and apparatus for receiving a stream of data values from a data medium, wherein the received data values correspond to ideal values but may include added noise that is dependent on previous noise and dependent on data on the data medium, said ideal values being determined by possible values of data on the medium, and for outputting information specifying a sequence of states corresponding to the stream of received data values, said sequence of states corresponding to possible data values on the medium, the apparatus comprising: a first detector, for calculating state sequence likelihood information based on a first noise model and received data values, and for providing said state sequence likelihood information to a second detector; a second detector for calculating weighting values indicating likelihoods that a data value received at a particular time corresponds to a particular state transition, using a second noise model, received data values, and state sequence likelihood information from the fi

Abstract: A calculator for use in a maximum likelihood detector, including: a receiver for receiving convolution encoded data which may include noise; first calculator for calculating a first component of a first path metric difference between two possible sequences of states corresponding to the convolution encoded data, the two sequences each having a length equal to a constraint length of the convolution encoded data, and the two sequences starting at a same state and ending at a same state, adapted to calculate the first component using the convolution-encoded data and using convolution encoding parameters of the convolution-encoded data, wherein the first component is independent of the two sequences; and second calculator for calculating a second component of the first path metric difference using the two sequences, wherein the second component is independent of the convolution encoded data; and using the first and second components to obtain the first path metric difference.

Abstract: A method and apparatus for receiving a stream of data values from a data medium, wherein the received data values correspond to ideal values but may include added noise that is dependent on previous noise and dependent on data on the data medium, said ideal values being determined by possible values of data on the medium, and for outputting information specifying a sequence of states corresponding to the stream of received data values, said sequence of states corresponding to possible data values on the medium, the apparatus comprising: a first detector, for calculating state sequence likelihood information based on a first noise model and received data values, and for providing said state sequence likelihood information to a second detector; a second detector for calculating weighting values indicating likelihoods that a data value received at a particular time corresponds to a particular state transition, using a second noise model, received data values, and state sequence likelihood information from the fi

Abstract: A maximum likelihood detector receiving a data stream corresponding to ideal values which may include noise, and outputting information specifying a sequence of states of maximum likelihood selected from possible states corresponding to the data stream according to weighting value selections made by the processors, the ideal values being determined by the possible states, including: a pre-processor to obtain first weighting values; processors in a hierarchy, each processor in a select level of the hierarchy is programmed to use, respectively, a plurality of the weighting values to calculate subsequent weighting values indicating respective likelihoods that a section of the data stream values corresponds to each of a plurality of possible state sequences, for each possible initial state and each possible final state, to select further weighting value of highest likelihood corresponding to a state sequence from the initial state to the final state.

Abstract: A calculator for use in a maximum likelihood detector, including: a receiver for receiving convolution encoded data which may include noise; first calculator for calculating a first component of a first path metric difference between two possible sequences of states corresponding to the convolution encoded data, the two sequences each having a length equal to a constraint length of the convolution encoded data, and the two sequences starting at a same state and ending at a same state, adapted to calculate the first component using the convolution-encoded data and using convolution encoding parameters of the convolution-encoded data, wherein the first component is independent of the two sequences; and second calculator for calculating a second component of the first path metric difference using the two sequences, wherein the second component is independent of the convolution encoded data; and using the first and second components to obtain the first path metric difference.

Abstract: A maximum likelihood detector receiving a data stream corresponding to ideal values which may include noise, and outputting information specifying a sequence of states of maximum likelihood selected from possible states corresponding to the data stream according to weighting value selections made by the processors, the ideal values being determined by the possible states, including: a pre-processor to obtain first weighting values; processors in a hierarchy, each processor in a select level of the hierarchy is programmed to use, respectively, a plurality of the weighting values to calculate subsequent weighting values indicating respective likelihoods that a section of the data stream values corresponds to each of a plurality of possible state sequences, for each possible initial state and each possible final state, to select further weighting value of highest likelihood corresponding to a state sequence from the initial state to the final state.

Abstract: A logic circuit for performing modular multiplication of a first multi-bit binary number and a second multi-bit binary number is provided. Combination logic combines the second multi-bit binary value with a group of W bits of the first multi-bit binary value every jth input cycle to generate W multi-bit binary combination values every jth input cycle, where the W bits comprise bits jW to (jW+W−1), W>1, j is the cycle index from 0 to k−1, k=N/W, and N is the number of bits of the first multi-bit binary value. Thus in this way a plurality of multi-bit binary combinations are input every cycle in a parallel manner. Accumulation logic holds a plurality of multi-bit binary values accumulated over previous cycles. Reduction logic generates a W bit value &Lgr; in a current cycle for use in the next cycle. A multi-bit modulus binary value is received and combined with the W bit value &Lgr; generated in a current cycle to generate W multi-bit binary values for use in the next cycle.