Low-Complexity Chase Decoding of Reed-Solomon Codes Using Channel Evaluation.

A novel time-varying channel adaptive low-complexity chase (LCC) algorithm with low redundancy is proposed, where only the necessary number of test vectors (TVs) are generated and key equations are calculated according to the channel evaluation to reduce the decoding complexity. The algorithm evaluates the error symbol numbers by counting the number of unreliable bits of the received code sequence and dynamically adjusts the decoding parameters, which can reduce a large number of redundant calculations in the decoding process. We provide a simplified multiplicity assignment (MA) scheme and its architecture. Moreover, a multi-functional block that can implement polynomial selection, Chien search and the Forney algorithm (PCF) is provided. On this basis, a high-efficiency LCC decoder with adaptive error-correcting capability is proposed. Compared with the state-of-the-art LCC (TV = 16) decoding, the number of TVs of our decoder was reduced by 50.4% without loss of the frame error rate (FER) performance. The hardware implementation results show that the proposed decoder achieved 81.6% reduced average latency and 150% increased throughput compared to the state-of-the-art LCC decoder.

Analysis of Regression Algorithms with Unbounded Sampling.

In this letter, we study a class of the regularized regression algorithms when the sampling process is unbounded. By choosing different loss functions, the learning algorithms can include a wide range of commonly used algorithms for regression. Unlike the prior work on theoretical analysis of unbounded sampling, no constraint on the output variables is specified in our setting. By an elegant error analysis, we prove consistency and finite sample bounds on the excess risk of the proposed algorithms under regular conditions.

Nanoporous Carbon Materials Derived from Zanthoxylum Bungeanum Peel and Seed for Electrochemical Supercapacitors.

In order to prepare biomass-derived carbon materials with high specific capacitance at a low activation temperature (≤700 °C), nanoporous carbon materials were prepared from zanthoxylum bungeanum peels and seeds via the pyrolysis and KOH-activation processes. The results show that the optimal activation temperatures are 700 °C and 600 °C for peels and seeds. Benefiting from the hierarchical pore structure (micropores, mesopores, and macropores), the abundant heteroatoms (N, S, and O) containing functional groups, and plentiful electrochemical active sites, the PAC-700 and SAC-600 derive the large capacities of ~211.0 and ~219.7 F g-1 at 1.0 A g-1 in 6 M KOH within the three-electrode configuration. Furthermore, the symmetrical supercapacitors display a high energy density of 22.9 and 22.4 Wh kg-1 at 7500 W kg-1 assembled with PAC-700 and SAC-600, along with exceptional capacitance retention of 99.1% and 93.4% over 10,000 cycles at 1.0 A g-1. More significantly, the contribution here will stimulate the extensive development of low-temperature activation processes and nanoporous carbon materials for electrochemical energy storage and beyond.