1.14 Comments and Further Reading
Signal processing books sometimes target two distinct audiences. The most introductory treatments are typically adopted for “Signals and Systems” courses, while more advanced textbooks target “Digital Signal Processing” courses. This division can be observed in the two classic books [OWH96] and [OS09]. It is also used in the Schaum’s Outline Series (well-known for the many fully solved problems).
Regarding the name digital or discrete-time: the jargon is such that people call digital signal processing (DSP) many operations that should be considered discrete-time signal processing given the amplitude is not quantized.23
There are many great books on DSP and three of them are (always check for new editions): [DdSN10, Lyo10, Mit10]. Youtube has several channels with videolectures about signal processing such as the ones by Prof. Barry Van Veen [ url1you].
When reading DSP and telecommunication books, keep in mind that the taxonomy of signals adopted here is not the only one used. For example, books such as [Pee86, Lat78] define digital signals as the ones with quantized amplitudes. Their alternative definition considers that , a continuous-time signal, is digital because of its quantized amplitudes.
Topics such as sampling and quantization have been widely investigated. The sampling theorem is part of a broad area. Only periodic sampling is discussed here. There are many other sampling theorems, addressing issues such as non-uniform sampling and non-bandlimited signals. See, e. g., [Mar01, BF01]. In [Pee86] a whole chapter is dedicated to sampling. As a side note: the sampling theorem is related to the work by Harry Nyquist and, therefore, called Nyquist theorem by some authors. However, the credits for the theory related to the sampling theorem should also go to C. Shannon, V. Kotelnikov, E. Whittaker and others. See, for example, [BS92, Luk99], for historical information.
As discussed in [Can21], to be more pedagogical, signal processing textbooks typically do not adopt rigorous mathematical treatment of continuous-time impulses. This was the approach adopted in this text.
Quantization is also part of a vast area known as source coding. A classical and good book is [JN84]. A more recent book is [AM07].
Regarding quantization, it is important to warn the experienced reader that in this text, unless otherwise stated (e. g., when discussing PAM decoding), it is assumed the quantizers are uniform and mid-tread. Non-uniform and mid-riser quantizers (see [JN84]) are not discussed.