Abstract
Based on a modified Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood channel equalizer, which is a block signal processing algorithm, for the detection of binary sequences transmitted through an unknown slowly time-varying channel. Both computational load and storage required by the proposed adaptive channel equalizer are linearly rather than exponentially proportional to the size of signal processing block. A simulation example is provided to support that it can simultaneously track the variation of slowly time-varying channels and detect unknown binary sequences well.