首页|New Machine Learning Study Findings Recently Were Reported by Researchers at Xid ian University (Machine-learning-based Source Number Estimation Under Unknown Sp atially Correlated Noise)
New Machine Learning Study Findings Recently Were Reported by Researchers at Xid ian University (Machine-learning-based Source Number Estimation Under Unknown Sp atially Correlated Noise)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting from Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “The existing model-d riven methods for source number estimation (SNE) under spatially correlated nois e are limited by the inherent shortcomings of model assumptions and subjective p arameter settings, and have high requirements for signal-to-noise ratio (SNR) an d sample size. Although machine learning (ML) has begun to emerge in SNE due to its powerful learning ability, existing ML-based methods mainly focus on Gaussia n white noise, and there are a few works on spatially correlated noise.”
Xi'anPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningXidian University
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