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What follows is one person's response to the perennial question "How do I learn DSP?" It was written by Dale Grover , with input from folks including Rick Lyons, Randy Yates, and Grant Griffin, though their participation is not an endorsement of every opinion expressed here--they're just good guys. A disclaimer: I am a co-author of one of the books mentioned. Introduction: What do you want to know? What do you know now? The three necessary elements 1. Books Non-traditional Online Tutorials Classics 2. Software Octave, Matlab, & relatives DSP-specific Symbolic General purpose 3. Hardware Formal courses A brief overview of DSP topics About this document What Do You Want to Know? What Do You Know Now? The best way to learn digital signal processing (DSP) depends on your goals and background. Why is this? - - - - - - - - - - - - - - In the past--in fact, until a few years ago--DSP was taught (and books were written) almost exclusively for people with an electrical engineering background. If that's your background, you have plenty of options in learning about DSP, and the resources noted in this document will give you plenty of choices. But if you don't have an electrical engineering background, there are now some books (and courses) that can bring you up to speed on basic DSP topics, and even on implementation issues. More about these options in a moment, when we discuss books. There are some folks--myself included--who claim that we should treat DSP in a similar way with how statistics is taught. Instead of claiming that every person who wants to know a little about statistics has to learn Everything There Is To Know about statistics, there are instead statistics courses for humanities majors, engineers, mathematics majors, and so on. Why? Because statistics is useful in many fields, and a useful subset of statistics can be taught to and used by folks even if they haven't studied all the theory behind statistics. In much the same way (actually, in a very deep sense), DSP has these same characteristics. DSP is, of course, useful, and indeed most anyone can learn the basics of DSP--and successfully apply these tools in their field. This document outlines some resources and approaches to do just that. Like statistics, there are trade offs between the size of the toolbox (and your skill in using those tools) and the amount of study and background required. At one extreme, you can end up with just the step-by-step "recipe" without any need to understand what's going on. At the other extreme, you can reach the point where you can select techniques from a wide array of possibilities, or even create your own, though this will require a good background in mathematics and so on. Your interests and backgrounds will be different from everyone else, and there is no single path to "DSP enlightenment"--or even "DSP familiarity."

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