21 Computing environments for Digital Signal processing 21.1 MATLAB Environment 21.2 Example 1: Signal Analysis Delores m. etter 21.3 Example 2: Filter Design and Analysis University of Colorado 21.4 Example 3: Multirate Signal Processing Computing environments provided by many software tools and packages allow users to design, simulate, and implement digital signal processing(DSP) techniques with speed, accuracy, and confidence. with access to libraries of high-performance algorithms and to advanced visualization capabilities, we can design and analyze systems using the equations and notations that we use to think about signal processing problems; we do not have to translate the equations and techniques into a different notation and syntax. The graphics interface provides an integral part of this design environment, and is accessible from any point within our algorithms within this type of computing environment, we are more productive. But, even more important, we develop ter solutions because we have so many more tools for analyzing solutions, for experimenting with"what if questions, and for developing extensive simulations to test our solutions. To illustrate the power of these environments,we present a brief description of MATLAB, one of the most popular technical computing environments in both industry and academia, and then present three examples that use MATLaB 21.1 MATLAB Environment MATLAB is an integrated technical environment designed to provide accelerated DSP design capabilities. In addition to the basic software package that contains powerful functions for numeric computations, advanced graphics and visualization capabilities, a high-level programming language, and tools for designing graphical user interfaces( GUD), MATLAB also provides a number of application-specific toolboxes that contain special ized libraries of functions. The discussion and examples that follow in this article use capabilities from the Signal Processing Toolbox. Other toolboxes that are applicable to solving signal processing problems include the following: Control Systems, Frequency Domain System Identification, Fuzzy Logic, Higher-Order Spectral Analysis, Image Processing, LMI (Linear Matrix Inequality)Control, Model Predictive Control, u-Analysis and Synthesis, Neural Networks, Optimization, Partial Differential Equations, QFT(Quantitation Feedback Theory) Control, Robust Control, Signal Processing, Splines, Statistics, Symbolic Math, System Identification, and Wavelets An interactive environment for modeling, analyzing, and simulating a wide variety of dynamic systems is also provided by MATLAB through SIMULINK--a graphical user interface designed to construct block diagram c 2000 by CRC Press LLC© 2000 by CRC Press LLC 21 Computing Environments for Digital Signal Processing 21.1 MATLAB Environment 21.2 Example 1: Signal Analysis 21.3 Example 2: Filter Design and Analysis 21.4 Example 3: Multirate Signal Processing Computing environments provided by many software tools and packages allow users to design, simulate, and implement digital signal processing (DSP) techniques with speed, accuracy, and confidence. With access to libraries of high-performance algorithms and to advanced visualization capabilities, we can design and analyze systems using the equations and notations that we use to think about signal processing problems; we do not have to translate the equations and techniques into a different notation and syntax. The graphics interface provides an integral part of this design environment, and is accessible from any point within our algorithms. Within this type of computing environment, we are more productive. But, even more important, we develop better solutions because we have so many more tools for analyzing solutions, for experimenting with “what if” questions, and for developing extensive simulations to test our solutions. To illustrate the power of these environments, we present a brief description of MATLAB, one of the most popular technical computing environments in both industry and academia, and then present three examples that use MATLAB. 21.1 MATLAB Environment MATLAB is an integrated technical environment designed to provide accelerated DSP design capabilities. In addition to the basic software package that contains powerful functions for numeric computations, advanced graphics and visualization capabilities, a high-level programming language, and tools for designing graphical user interfaces (GUI), MATLAB also provides a number of application-specific toolboxes that contain special￾ized libraries of functions. The discussion and examples that follow in this article use capabilities from the Signal Processing Toolbox. Other toolboxes that are applicable to solving signal processing problems include the following: Control Systems, Frequency Domain System Identification, Fuzzy Logic, Higher-Order Spectral Analysis, Image Processing, LMI (Linear Matrix Inequality) Control, Model Predictive Control, m-Analysis and Synthesis, Neural Networks, Optimization, Partial Differential Equations, QFT (Quantitation Feedback Theory) Control, Robust Control, Signal Processing, Splines, Statistics, Symbolic Math, System Identification, and Wavelets. An interactive environment for modeling, analyzing, and simulating a wide variety of dynamic systems is also provided by MATLAB through SIMULINK—a graphical user interface designed to construct block diagram Delores M. Etter University of Colorado