首页|Study Results from Texas A&M University Update Understanding of Mac hine Learning (Multi-channel Nonlinearity Mitigation Using Machine Learning Algo rithms)
Study Results from Texas A&M University Update Understanding of Mac hine Learning (Multi-channel Nonlinearity Mitigation Using Machine Learning Algo rithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News - Research findings on Machine Learning are discuss ed in a new report. According to news reporting out of College Station, Texas, b y NewsRx editors, research stated, “This paper investigates multi-channel machin e learning (ML) techniques in the presence of receiver nonlinearities and noise, and compares the results with the single-channel receiver architecture. It is k nown that the multi-channel architecture relaxes the sampling speed requirement of analog to digital conversion and provides significant robustness to clock jit ter and front-end noise due to the bandwidth-splitting property inherent in thes e receivers.”
College StationTexasUnited StatesN orth and Central AmericaAlgorithmsCyborgsEmerging TechnologiesMachine Le arningTexas A&M University
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