3.1 Discrete-Time Fourier Transform Definition- The discrete-time Fourier transform (DTFT) X(eio) of a sequence x[n] is given by jae In general,() is a complex function of the real variable and can be written as X(eio) Xre(eio) +j Xim(eio)
6.1 Introduction The convolution sum description of an LTI discrete-time system can, in principle, be used to implement the system For an IR finite-dimensional system this approach is not practical as here the impulse response is of infinite length · However, direct implementation of the IIR finite-dimensional system is practica
Objective-Determination- of realizable transfer function G() approximating a given frequency response specification is an important step in the development of a digital filter If an IIR filter is desired, G() should be a stable real rational function Digital filter design is the process of deriving the transfer function G
§1.1 Introduction §1.2 Continue-time Signal §1.3 signal representation based on δ(t) §1.4 Linear time-invariant system §1.5 System unit impulse response §1.6 Fourier series of periodic signals §1.7 Fourier analyses of non-periodic signals—Fourier Transform §1.8 Fourier Transform of typical signals §1.9 Fourier Transform of typical signals §1.10 Properties of Fourier Transform §1.11 Fourier analyses of linear system
§2.1 Discrete-Time Signals: Time-Domain Representation §2.2 Operations on Sequences §2.3 Basic Sequences §2.4 The Sampling Process §2.5 Discrete-Time Systems §2.6 Time-Domain Characterization of LTI Discrete-Time System §2.7 Classification of LTI Discrete-Time Systems §2.8 Correlation of Signals
§5.1 Digital Processing of Continuous-Time Signals §5.2 Sampling of Continuous-time Signals §5.3 Effect of Sampling in the Frequency Domain §5.4 Recovery of the Analog Signal §5.5 Implication of the Sampling Process §5.6 Sampling of Bandpass Signals §5.7 Analog Lowpass Filter Specifications §5.8 Analog Lowpass Filter Design