Abstract: Error correcting codes of any distance (including codes of distance greater than four) use only exclusive OR (XOR) operations. Any code over a finite field of characteristic two are converted into a code whose encoding and correcting algorithms involve only XORs of words (and loading and storing of the data). Thus, the implementation of the encoding and correcting algorithms is more efficient, since it uses only XORs of words—an operation which is available on almost all microprocessors. An important code, the (3, 3) code of distance four, is also described.

Abstract: An efficient method for finding all the possible corrections of a bust of length b and e random errors consists of finding a polynomial whose roots are the candidate location for l—the location of the beginning of the burst—thus avoiding the search over all possible values of l (it is assumed that the burst is non-trivial, i.e., at least one of its errors has a non-zero value). In order to reduce the number of spurious solutions, it is assumed that the number of syndromes is t=2e+b+s, where s is at least 2. The larger the value of s the less likely it is that the algorithm will generate “spurious” solutions. Once the location of the burst is known, standard procedures are used to determine the magnitudes of the burst errors and the location and magnitude of the random errors.

Abstract: The Hamming distance of an array of storage devices is increased by generating a parity check matrix based on column equations that are formed using an orthogonal parity code and includes a higher-order multiplier that changes each column. The higher order multiplier is selected to generate a finite basic field of a predetermined number of elements. The array has M rows and N columns, such that M is greater than or equal to three and N is greater than or equal to three. Row 1 through row M?2 of the array each have n–p data storage devices and p parity storage devices. Row M?1 of the array has n?(p+1) data storage devices and (p+1) parity storage devices. Lastly, row M of the array has N parity storage devices.

Abstract: An error correction algebraic decoder and an associated method correct a combination of a B-byte burst of errors and t-byte random errors in a failed sector, by iteratively adding and removing an erasure (N?B) times until the entire failed sector has been scanned, provided the following inequality is satisfied: (B+2t)?(R?1), where N denotes the number of bytes, B denotes the length of the burst of errors, t denotes the total number of random errors, and R denotes the number of check bytes in the failed sector. This results in a corrected sector at a decoding latency that is a generally linear function of the number of the check bytes R, as follows: Decoding Latency=5R(N?B).

Abstract: Error correcting codes of any distance (including codes of distance greater than four) use only exclusive OR (XOR) operations. Any code over a finite field of characteristic two are converted into a code whose encoding and correcting algorithms involve only XORs of words (and loading and storing of the data). Thus, the implementation of the encoding and correcting algorithms is more efficient, since it uses only XORs of words—an operation which is available on almost all microprocessors. An important code, the (3, 3) code of distance four, is also described.

Abstract: An efficient method for finding all the possible corrections of a bust of length b and e random errors consists of finding a polynomial whose roots are the candidate location for l— the location of the beginning of the burst—thus avoiding the search over all possible values of l (it is assumed that the burst is non-trivial, i.e., at least one of its errors has a non-zero value). In order to reduce the number of spurious solutions, it is assumed that the number of syndromes is t=2e+b+s, where s is at least 2. The larger the value of s the less likely it is that the algorithm will generate “spurious” solutions. Once the location of the burst is known, standard procedures are used to determine the magnitudes of the burst errors and the location and magnitude of the random errors.

Abstract: An error correction algebraic decoder uses a key equation solver for calculating the roots of finite field polynomial equations of degree up to six, and lends itself to efficient hardware implementation and low latency direction calculation. The decoder generally uses a two-step process. The first step is the conversion of quintic equations into sextic equations, and the second step is the adoption of an invertible Tschirnhausen transformation to reduce the sextic equations by eliminating the degree 5 term. The application of the Tschirnhausen transformation considerably decreases the complexity of the operations required in the transformation of the polynomial equation into a matrix. The second step defines a specific Gaussian elimination that separates the problem of solving quintic and sextic polynomial equations into a simpler problem of finding roots of a quadratic equation and a quartic equation.

Abstract: An error correction algebraic decoder and an associated method correct a combination of a B-byte burst of errors and t-byte random errors in a failed sector, by iteratively adding and removing an erasure (N−B) times until the entire failed sector has been scanned, provided the following inequality is satisfied: (B+2t)≦(R−1), where N denotes the number of bytes, B denotes the length of the burst of errors, t denotes the total number of random errors, and R denotes the number of check bytes in the failed sector. This results in a corrected sector at a decoding latency that is a generally linear function of the number of the check bytes R, as follows: Decoding Latency=5R(N−B).

Abstract: A Hilbert transform is used to process perpendicular magnetic recording signals from both single layer and dual layer disks to produce a complex analytic signal. This complex analytic signal is used to derive angles of magnetization, which depend on the distance between recorded magnetic transitions and consequently which can be used in error estimation. Moreover, the Hilbert transform in cooperation with an equalizer FIR optimizes transformation of the signal such that conventional longitudinal recording processing methods can subsequently be used to process the signal that is read back from the magnetic recording medium.

Abstract: An on-the-fly algebraic error correction system and corresponding method for reducing error location search are presented. The method transforms an error locator polynomial into two transformed polynomials whose roots are elements in a smaller subfield, in order to significantly simplify the complexity, and to reduce the latency of the error correcting system hardware implementation. More specifically, if the error locator polynomial is over a finite field of (22n) elements, the transformed polynomial is over a finite subfield of (2n) elements. Thus, the problem of locating the roots of the error locator polynomial is reduced to locating the roots of the transformed polynomials. Assuming the error locator polynomial is of degree m, the present method requires at most (m2/2) evaluations of polynomials over the Galois field GF(22n) and (2n+1) evaluations over the subfield GF(2n) or root finding of two polynomials of at most a degree m over the subfield GF(2n).

Abstract: A system and method for algebraically correcting errors in complex digitized phase signals from a magneto-resistive or giant magneto-resistive (MR/GMR) head readback waveform includes a data state machine that encodes phase symbols into data bits in accordance with, e.g., the (1, 10) constraint and a parity state machine that generates parity symbols such that a single inserted parity symbol does not violate the (1, 7) constraint in a run length limited code and furthermore the data following the insertion will not violate the (1, 10) constraint in a run length limited code. The state machines can be used as a trellis to perform maximum likelihood decoding on received coded data, thus performing soft algebraic error detection on received data. The invention thus guarantees better overall error rate performance than hard decision post processing of blocks of detected bits by a parity check matrix which is otherwise vulnerable to loss of bit synchronization at high linear density recording.

Abstract: A soft error correction algebraic decoder and an associated method use erasure reliability numbers to derive error locations and values. More specifically, symbol reliability numbers from a maximum likelihood (ML) decoder as well as a parity check success/failure from inner modulation code symbols are combined by a Reed-Solomon decoder in an iterative manner, such that the ratio of erasures to errors is maximized. The soft error correction (ECC) algebraic decoder and associated method decode Reed Solomon codes using a binary code and detector side information. The Reed Solomon codes are optimally suited for use on erasure channels. A threshold adjustment algorithm qualifies candidate erasures based on a detector error filter output as well as modulation code constraint success/failure information, in particular parity check or failure as current modulation codes in disk drive applications use parity checks. This algorithm creates fixed erasure inputs to the Reed Solomon decoder.

Abstract: A circuit combines a read signal from an MR/GMR read head with a signal generated by a matched filter, the parameters of which depend on the geometry of the head and the output of which, generated every Nth clock period, includes a real part and an imaginary part that models an expected head response. The combined signal is phase equalized and sent to a complex correlator, which integrates the signal over N clock periods to output a correlated signal having real and imaginary portions of the Nth root of unity which correspond to bits in an N-clock data unit. The real and imaginary portions can subsequently be digitized and analyzed for errors.

Abstract: An error correction algebraic decoder uses a key equation solver for calculating the roots of finite field polynomial equations of degree up to six, and lends itself to efficient hardware implementation and low latency direction calculation. The decoder generally uses a two-step process. The first step is the conversion of quintic equations into sextic equations, and the second step is the adoption of an invertible Tschirnhausen transformation to reduce the sextic equations by eliminating the degree 5 term. The application of the Tschirnhausen transformation considerably decreases the complexity of the operations required in the transformation of the polynomial equation into a matrix. The second step defines a specific Gaussian elimination that separates the problem of solving quintic and sextic polynomial equations into a simpler problem of finding roots of a quadratic equation and a quartic equation.

Abstract: A Hilbert transform is used to process perpendicular magnetic recording signals from both single layer and dual layer disks to produce a complex analytic signal. This complex analytic signal is used to derive angles of magnetization, which depend on the distance between recorded magnetic transitions and consequently which can be used in error estimation. Moreover, the Hilbert transform in cooperation with an equalizer FIR optimizes transformation of the signal such that conventional longitudinal recording processing methods can subsequently be used to process the signal that is read back from the magnetic recording medium.

Abstract: A computationally efficient, machine-implementable method and means for detecting and correcting errors in received codewords on-the-fly within the capacity of a linear cyclic code using ultra-fast error location processing. Each error locator polynomial of degree t over a finite Galois field derived from a codeword syndrome is mapped into a matrix representative of a system of linear simultaneous equations related to the polynomial coefficients. Roots indicative of error locations within the codeword are extracted from the matrix by a modified Gaussian Elimination process for all the roots where t≦5 and at least one root plus a subset of candidate roots from the finite field for iterative substitution where t>5. Corrected values are separately determined and correction is secured by logically combining the corrected values with the codeword values in error at the error locations represented by the roots.

Abstract: A method and means for enhancing the error detection and correction capability obtained when a plurality of data byte strings are encoded in a two-level, block-formatted linear code using code word and block-level redundancy. This is accomplished by vector multiplication of N data byte vectors and a nonsingular invertible integration matrix with nonzero minors with order up to B to secure the necessary interleaving among N data byte vectors to form modified data byte vectors. The selected patterns of interleaving ensure single-pass, two-level linear block error correction coding when the modified data vectors are applied to an ECC encoding arrangement. The method and means are parameterized so as to either extend or reduce the number of bursty codewords or subblocks to which the block-level check bytes can be applied.

Abstract: A method and means for reducing high-duty-cycle unconstrained binary signal sequences in storage and communications processes and systems by invertibly mapping such sequences into a (1, k) rate ⅔ RLL codestream constrained to a duty cycle substantially approximating one-third. That is, binary sequences ordinarily mapping into high-duty-cycle RLL-code sequences are either inhibited from repeating indefinitely or excluded.

Abstract: A computationally efficient, machine-implementable method and means for detecting and correcting errors in received codewords on-the-fly within the capacity of a linear cyclic code using ultra-fast error location processing. Each error locator polynomial of degree t over a finite Galois field derived from a codeword syndrome is mapped into a matrix representative of a system of linear simultaneous equations related to the polynomial coefficients. Roots indicative of error locations within the codeword are extracted from the matrix by a modified Gaussian Elimination process for all the roots where t.ltoreq.5 and at least one root plus a subset of candidate roots from the finite field for iterative substitution where t>5. Corrected values are separately determined and correction is secured by logically combining the corrected values with the codeword values in error at the error locations represented by the roots.

Abstract: The invention relates to an arithmetic unit (AU) in combination with an algebraic block ECC decoder for controlling errors in an electronically recorded digital data message by performing at least one of a plurality of predetermined arithmetic operations on the data message in one or more of a plurality of subfields of a first GF(2.sup.12) or a second GF(2.sup.8) finite field. The arithmetic operations are selected either from a first group of operations associated with a first subfield GF(2.sup.4) as cubically extended to the first finite field GF(2.sup.12) or as quadratically extended to the second finite field GF(2.sup.8), or selected from a second group of operations associated with a second subfield GF(2.sup.6) as quadratically extended to the first finite field GF(2.sup.12).