## Principles of Coding: Filtering, and Information Theory |

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a-priori knowledge a-priori probabilities alphabet amplitude assumed auto-correlation function bandwidth bility binary erasure channel binary symmetric channel channel capacity check digits code group code points comb filter communication systems component computed continuous information correction correlation cross-correlation cross-correlation function decision feedback Decision-Feedback System defined density function detection detector discrete effect ensemble equal equation erasure error probability error-free feedback channel feedback system Fourier frequency Gaussian noise given Hence impulsive response inductive probability infinite information rate Information Theory Institute of Radio integral linear log2 p(x matched filter maximize measure noise power noise voltage null zone null-zone number of samples observation operation optimum output signal-to-noise ratio parity check periodic function perturbed possible power spectrum proba problem radar random functions received signal reliability repetitive result Shannon-Fano code signal and noise signal space signal-to-noise ratio Signal-to-Noise Ratio rms single error specified statistical symbols Theorem threshold tion transmission white Gaussian noise