Mathematics behind Signal and Systems

In summary: He prefers a book that reviews all the necessary mathematical analysis topics before diving into the main content. He is interested in finding the equivalent of "A Mathematical Introduction to Signal and Systems" by A. D. Lewis. He asks for any recommendations and suggests the "Digital Signal Processing" ebook from CERN Accelerator School. Someone suggests the "Fourier Transform" as a starting point for becoming an expert. After some research, it is suggested that the notes by Lewis may not be rigorous enough and instead recommends "Fourier Analysis and its Applications" by Gasquet and Witomski. In summary, Jason is looking for a rigorous signal processing textbook
  • #1
amg63
8
2
I am looking for a signal processing textbook that uses real, complex, and functional analysis with measure theory. In other words, mathematically rigorous signal processing. Specifically, I prefer the kind that takes time to review all the topics from mathematical analysis before jumping into the fire (due to a potential experience deficit in some analysis topics), but will gladly consider any rigorous signal processing. A Mathematical introduction to signal and systems by A. D. Lewis is pretty much what I am looking for, however, only first volume is available, so I need an equivalent. Please inform me of any textbooks that you know of that fit my search criteria, and I shall be grateful in return. Thank you for your time.
 
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  • #2
  • #3
Google the Fourier Transform and become an expert at that.
 
  • #4
I think this is the book you are looking for: http://www.fourierandwavelets.org/FSP_v1.1_2014.pdf

EDIT: After looking at the text you posted perhaps my suggestion is not rigorous enough.

Note to moderators this version of the book is posted for free distribution on the author's website.
 
  • #5
I wasn't familiar with the notes by Lewis, but was intrigued so googled. I found the second volume on the author's web site.
http://www.mast.queensu.ca/~andrew/
Follow the link to course notes, then math 334.

One book I really like is "Fourier Analysis and its applications" by Gasquet and Witomski. It is probably not advanced enough for you; it is certainly less advanced (and shorter!) than the notes by Lewis, but is more polished. I especially like the treatment of Fourier analysis and distribution theory.

Jason
 

1. What is the importance of mathematics in understanding signal and systems?

The field of signal and systems relies heavily on mathematics to analyze and model various signals and systems. Mathematics provides the necessary tools and techniques to understand the behavior of signals and systems, make predictions, and design systems that can manipulate signals in a desired way.

2. Can you explain the concept of signals in terms of mathematics?

Signals can be represented mathematically as functions of time or space. These functions can be continuous or discrete, and can be described using various mathematical representations such as differential equations, Fourier series, or Laplace transforms.

3. How do mathematical transformations like Fourier and Laplace transforms play a role in signal and systems analysis?

Transformations like Fourier and Laplace transforms are essential tools in signal and systems analysis. They allow us to convert signals from the time or space domain to the frequency or complex domain, respectively. This makes it easier to analyze signals and systems and understand their behavior.

4. What are some common techniques used in mathematics to analyze signals and systems?

Some common techniques used in mathematics to analyze signals and systems include differential equations, linear algebra, Fourier analysis, and complex analysis. These techniques are used to model signals and systems, solve equations, and understand the behavior of signals and systems over time or in different domains.

5. How does mathematics play a role in designing systems for signal processing?

Mathematics is crucial in designing systems for signal processing. It allows us to model and analyze signals and systems, design filters and other components to manipulate signals, and optimize system performance. Mathematics also helps in understanding the limitations and trade-offs in system design and choosing the most efficient solutions.

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