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Extra info for Advanced Digital Signal Processing and Noise Reduction, Third Edition

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1960) A new approach to linear filtering and prediction problems. Trans. ASME Ser. D J. Basic Engng, 82: 35–45. M. (1993) Fundamentals of Statistical Signal Processing, Estimation Theory. Prentice-Hall, Englewood Cliffs, NJ. S. (1983) Speech Enhancement. Prentice Hall, Englewood Cliffs, NJ. , Salz J. J. (1968) Principles of Data Communications. McGraw-Hill, New York. Y. (1993) Digital Neural Networks. Prentice-Hall, Englewood Cliffs, NJ. L. (1987) Digital Spectral Analysis with Applications. Prentice-Hall, Englewood Cliffs, NJ.

10) where bˆ m is an estimate of the binary state indicator sequence b m , and may be erroneous, particularly if the signal-to-noise ratio is low. 1 lists four possible outcomes that, together, b m and its estimate, bˆ m , can assume. The choice of the threshold level affects the sensitivity of the detector. The higher the threshold, the lower the likelihood that noise would be classified as signal is, so the false alarm rate falls, but the probability of misclassification of signal as noise increases.

1 ADAPTIVE NOISE CANCELLATION In speech communication from a noisy acoustic environment such as a moving car or train, or over a noisy telephone channel, the speech signal is observed in an additive random noise. 3 A classification of the applications of digital signal processing. 6 INTRODUCTION In signal measurement systems the information-bearing signal is often contaminated by noise from its surrounding environment. 3) where x m and n m are the signal and the noise, and m is the discrete-time index.

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