Abstract: The current invention involves a forward error detection system, especially for use with Low Density Parity Check codes. A parallel SISO structure allows the decoder to process multiple parity equations at the same time. There is a new SISO decoder which allows for the updating of the Log-likelihood-ratios in a single operation, as opposed to the two pass traditionally associated with the Tanner Graphs. In the decoder, there is a mapping structure that correctly aligns the stored estimates, the stored differences and the SISOs. There is also the ability to deal with multiple instances of the same data being processed at the same time. This structure manages the updates and the differences in such a manner that all calculations on a single piece of data that are processed in parallel are incorporated correctly in the new updated estimates.

Abstract: The current invention involves a forward error detection system, especially for use with Low Density Parity Check codes. A parallel SISO structure allows the decoder to process multiple parity equations at the same time. There is a new SISO decoder which allows for the updating of the Log-likelihood-ratio's in a single operation, as opposed to the two pass traditionally associated with the Tanner Graph's. In the decoder, there is a mapping structure that correctly aligns the stored estimates, the stored differences and the SISO's. There is also the ability to deal with multiple instances of the same data being processed at the same time. This structure manages the updates and the differences in such a manner that all calculations on a single piece of data that are processed in parallel are incorporated correctly in the new updated estimates.

Abstract: The current invention involves a forward error detection system, especially for use with Low Density Parity Check codes. A parallel SISO structure allows the decoder to process multiple parity equations at the same time. There is a new SISO decoder which allows for the updating of the Log-likelihood-ratio's in a single operation, as opposed to the two pass traditionally associated with the Tanner Graph's. In the decoder, there is a mapping structure that correctly aligns the stored estimates, the stored differences and the SISO's. There is also the ability to deal with multiple instances of the same data being processed at the same time. This structure manages the updates and the differences in such a manner that all calculations on a single piece of data that are processed in parallel are incorporated correctly in the new updated estimates.

Abstract: A sliding window with big gap data compression system is simple to implement and gives good compression over a wide variety of bilevel images. A sliding window compressor with a very small window size is utilized in conjunction with a storage buffer which is large enough to hold at least an entire scan line of data symbols. Coupled to the storage buffer is circuitry that checks for a match between the incoming data symbol and a symbol stored in one specific programmable location. This programmable location is preferably exactly one scan line length away. Match locations are either within the range of the small window or exactly equal to the specific programmable location. The entire compressor can be viewed as a sliding window with a big gap (SWBG). This sliding window is of a length corresponding to the length of the scan line, comprised of the small window followed by a big gap and then the one specific programmable location, at the end of the scan line.

Abstract: An adaptive lossless data compression system with systolic string matching logic performs compression and decompression at the maximum rate of one symbol per clock cycle. The adaptive data compression system uses an improvement of the LZ1 algorithm. A content addressable memory (CAM) is used to store the last n input symbols. The CAM is stationary, stored data is not shifted throughout the CAM, but rather the CAM is used as a circular queue controlled by a Write Address Pointer Counter (WREN). During a compression operation, a new input symbol may be written to the CAM on each clock cycle, while simultaneously the rest of the CAM is searched for the input symbol. Associated with each word of the CAM array is a String Match State Machine (SMSM) and, an address logic module (ALM). These modules detect the occurrence of strings stored in the CAM array that match the current input string and report the address of the longest matching string nearest to the Write Address Pointer.

Abstract: The present invention is for a Error Correction Unit (ECU) that uses a single stack architecture for the generation, reduction and evaluation of the polynomials involved in the correction of a Reed-Solomon code. The circuit uses the same hardware to generate the syndromes, reduce the .OMEGA.(x) and .LAMBDA.(x) polynomials and evaluate the .OMEGA.(x) and .LAMBDA.(x) polynomials. Some of the specifics involved in calculating and reducing the polynomials mentioned above are novel as well. First, the implementation of the general Galois field multiplier is new and faster than previous implementations. Second, the circuit for implementing the Galois field inverse function has not appeared in prior art designs. Third, a novel method of generating the .OMEGA.(x) and .LAMBDA.(x) polynomials (including alignment of these polynomials prior to evaluation) is utilized. Fourth, corrections are performed in the same order as they are received using a premultiplication step prior to evaluation.

Abstract: A Reed-Solomon Galois Field Euclid algorithm error correction decoder solves Euclid's algorithm with a Euclid stack which can be configured to function as a Euclid divide or a Euclid multiply module. The decorder is able to resolve twice the erasure errors by selecting .GAMMA.(x) and T(x) as the initial conditions for .LAMBDA..sup.(0) (x) and .OMEGA..sup.(0) (x), respectively.

Abstract: A Galois Field error correction decoder is described which can correct an error in a received polynomial. The apparatus includes means for generating a plurality of syndrome polynomials. A magnitude polynomial and a location polynomial having a first derivative are calculated from the syndrome polynomials utilizing Euclid's Algorithm. The module utilizing Euclid's Algorithm includes a general Galois Field multiplier having combinational logic circuits. The magnitude polynomial is divided by the first derivative of said location polynomial to form a quotient. Preferrably the division includes finding the inverse of the first derivative and multiplying the inverse by the magnitude polynomial. The error is corrected by exclusive ORing the quotient with the received polynomial.