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Digital signal processing is used in many application areas where a few years ago analogue circuits were the norm, e.g. digital radio. In addition to not suffering from the drift and non-linearity associated with analogue circuits the mathematical basis of DSP allows algorithms which have no counterpart in the analogue world. Of course DSP has its own problems associated with quantization, sampling rates, etc.

DSP requires a sound mathematical framework and the first two chapters review the Laplace transform, Hilbert spaces, Fourier transform, matrices and linear algebra (just to remind one of the forgotten maths lectures?) Chapter three starts by looking at the analogue world (from Ohm's law to network analysis and poles and zeros) and analogue filters, then moving onto digital representation and IIR filters (which use the same mathematics as analogue filters and suffer from the same problems). Chapter four discusses linear time-invariant and time-variant systems and digital filters (halfband, M-band, etc.) in detail and chapter five multi- resolution analysis and Wavlets (starting from stochastic analysis through to the FWT).

Assuming a good knowledge of engineering maths this book will give a sound grounding in DSP and would be suitable for a final year undergraduate module (note that FFTs are not covered!). The title is misleading (as Francis indicated in his review in C Vu January 1998), there is little C code, which is of poor quality, often inefficient and sparse commenting makes it very difficult to follow (functions do not even have comments describing the parameters). However, it is worth looking at for the DSP content!