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What is Adaptive Equalizer Training Optimization about?

This paper presents an algorithm designed to shorten the training period and adaptation time of an adaptive equalizer for time-invariant or slowly varying channels with white Gaussian noise. The algorithm employs a minimum mean-squared error criterion with variable step sizes and is compared to a fixed step-size algorithm, showing faster adaptation times despite increased complexity. Experimental results indicate that the new dynamic programming-based approach significantly reduces the training period compa

Author

yangzhen

Language

EN