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The Fast Fourier Transform has numerous applications in signal processing and communication. Utilizing the radix-2 time decimation algorithm, we suggest a new pipelining architecture for multipath delay commutators. Because the architecture puts a premium on optimising the intermediate data processing process, computing speed is increased while register usage is decreased. By combining CORDIC and binary decomposition coding, we propose a new approach to performing multiplication that does away with the traditional multiplier and multiplicand. The proposed FFT processor was built using TSMC's 90-nm CMOS technology. The proposed FFT processor reduces hardware complexity by 16 percent while increasing throughput by 16 percent, according to synthesis results, the proposed FFT processor increases throughput by 16% compared to existing architectures while simultaneously reducing hardware complexity by 16%. From our experiments, we can infer that, compared to other recently proposed implementations, ours uses less hardware and has lower latency. Many different speech processing applications make use of this processor. [ABSTRACT FROM AUTHOR]

Code parity-check matrix dimensions and a maximum distance restriction are generated by the Eigen structure of the Fourier number theoretic transform. Such codes may be deciphered using a given method. Error-correcting code Fourier codes are introduced. Shortened syndrome look-up tables are efficiently used in a manner that provides an improvement over conventional decoding methods for syndromes. One way to think about it is that it's an intriguing twist on the permutation decoding method that allows for permutations without maintaining the code. The functioning of non- binary LDPC codes is examined for various Galois Field orders and PCM topologies. Several potential code constructions aimed at the small block regime are discussed in this paper, alongside traditional error-correction coding systems and length performance limitations. Using an additive white Gaussian noise channel, this study investigates the application of binary and high-order modulation techniques over the noise. We will demonstrate how to use different performance vs. decoding complexity trade-offs to reach theoretical limits. Despite its decreased complexity, our revised decoder has a word error rate that is superior to current decoders. As the last step, we integrate our improved decoder with the traditional belief propagation method. Fast Fourier transforms (FFTs), regarded as the building blocks of all signal processing systems, may be accomplished utilizing the algorithm-based fault tolerance approach. In the best-case scenario, the suggested technique can detect numerous faults and correct multiple problems at the same time. The code may be used to encode two-dimensional data for usage in bar codes and data storage. The performance of non-binary LDPC codes is examined for various Galois Field orders and PCM topologies. The LDPC codes' robustness is defined by their parity check matrix (PCM). [ABSTRACT FROM AUTHOR]

In this paper, a new method of decoding binary linear block codes using soft decision decoding is presented. The primary concept behind this strategy is to gradually improve error performance over time. When near-optimal error performance or a desirable level of error performance has been attained for each decoding step, the decoding process ends. It's possible to choose between performance and decoding difficulty with greater freedom now. In order to decode the signals, it is recommended that they be reordered depending on the dependability level of each individual symbol. We examine the statistics of ordered noise in this work. The reprocessing technique is based on two monotonic features obtained from these statistics. Reprocessing the hard-decision-decoded codeword in consecutive stages until the required performance is obtained is the second step in decoding each codeword. Using a cost function, reprocessing is predicated on the ordering's monotonic features. [ABSTRACT FROM AUTHOR]