NEW—reorganizes coverage of DFT and FFT algorithm for greater clarity—now introduces the DFT and describes its efficient computation immediately following the treatment of Fourier analysis.
Describes the operations and techniques involved in the analog-to-digital conversion of analog signals.
Studies the characterization and analysis of linear time-invariant discrete-time systems and discrete- time signals in the time domain.
Considers both the bilateral and the unilateral z-transform, and describes methods for determining the inverse z-transform.
Analyzes signals and systems in the frequency domain, and presents Fourier series and Fourier transform in both continuous-time and discrete-time signals.
Treats the realization of IIR and FIR systems, including direct-form, cascade, parallel, lattice and lattice-ladder realizations.
Looks at the basics of sampling rate conversion and presents systems for implementing multirate conversion.
Offers a detailed examination of power spectrum estimation, with discussions on nonparametric and model-based methods, as well as eigen-decomposition- based methods, including MUSIC and ESPRIT.
Includes many examples throughout the book and with approximately 500 workable problems.
Perfect book. But not for reading. Every single thing is described in maximum detail by the authors; therefore, it is boring to read but great to find solutions. I consider this book being equivalent to stackoverflow.com for engineers.
Pros: This is the textbook for a DSP course at my university.
Cons: I find that the book contains numerous errors in mathematical notation, making it both confusing and time-consuming to interpret and understand.
For example, in the discrete-time system, the author denotes y(n) = T(x(n)), which is incorrect in function notation. From my perspective, the correct notation should be y(n) = [T(x)](n). Here, T(x) represents a mapping that operates on a sequence (either finite or infinite) and produces another sequence, y, with n serving as the index of the new sequence.
In addition, in the chapter Discrete-time signal and system, the author wrote the Convolution formula as y(n) = h(n) * x(n). This is a completely incorrect mathematical formulation. Even though the Convolution formulas on Wikipedia are defined more precisely (https://en.wikipedia.org/wiki/Convolu...).
There are numerous other mathematical errors.
If the author adhered more strictly to mathematical notation, I would be able to read and understand this book and its principles more quickly
Though not clear and intuitive in the first go, you see the beauty as you read and re-read. This is not an introductory text in Digital Signal Processing, some intuitions, or rather the required maturity, has to be formed before considering reading this book.
For a complete newbie to Digital Signal Processing, this was a clear and fun read. Notation was very clear, lots of examples, and good amount of topics covered. I used this alongside a Masters level SSP course with no prior signal theory experience and didn't get too lost - so the book did it's job as a student text!
Although it takes some getting used to, once you get comfortable with it, this is a great DSP text. Good explanations about the underlying math, and also some helpful practical examples of application. My first point of reference for DSP math.