FFT Tutorial and Applied DSP Magic: Cascade Polyphase Filter Banks

#"FFT #Tutorial #and #Applied #DSP #Magic: #Cascade #Polyphase #Filter #Banks" #by #Prof. #Fred #Harris #University #of #California #San #Diego #.
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  1. FFT Tutorial: A quick review of the major fast algorithms for computing the DFT: three primary forms, the Cooley-Tukey, the Good-Thomas, and the Winograd. We present a few essential equations and lots of figures and images that show why and how they differ. Which FFT algorithm is in your 4G phone? (Hint: it is not a radix-2 Cooley-Tukey. Why not?) Transforms come in other sizes besides powers of 2. If you have need for a 60 point FFT… don’t zero extend to 64, use the very efficient 60 point FFT: it is more efficient than the 64 point FFT. The eye opening and fun part of the presentation is a number of interesting applications of the FFT that are unrelated to power spectral estimation.
  2. Applied DSP Magic: Cascade Polyphase Filter Banks The polyphaser filter bank comes in two flavors. One does analysis and one does synthesis. These are opposite things. One partitions a broadband input signal into M baseband output signals. The other assembles a broadband output signal from M baseband input signals. What’s impressive is that they each accomplish their tasks with a single filter: not M copies of that filter, but one single filter. The second surprise! They do this counter-intuitive thing: they move spectral bands by aliasing them to and from baseband and then separating the multiple aliases. It seems aliasing is your friend. Have we gotten your attention yet? We then do something silly, to accomplish truly remarkable feats of signal processing, we cascade the analysis and synthesis filter banks. The things we can now accomplish include the formation of variable bandwidth filters without changing filter coefficients at orders of magnitude reduction in processing costs relative to their direct implementation. Convert 3-GHz input data stream into 60 parallel 50 MHz output data streams for processing with reduced cost, lower speed engines. Formation of multiple simultaneous channels with arbitrary bandwidths and center frequencies with similar impressive reductions in processing cost.

 


  Date and Time

  Location

  Hosts

  Registration


  • Date: 09 Oct 2018
  • Time: 06:00 PM UTC to 08:00 PM UTC
  • Add_To_Calendar_icon Add Event to Calendar
  • Fairleigh Dickinson University
  • Teaneck, New Jersey
  • United States 07666
  • Building: Auditorium M105, Muscarelle Center
  • Click here for Map
  • Contact Event Host

  • Hong Zhao (201)-692-2350, zhao@fdu.edu; Alfredo Tan, tan@fdu.edu, Howard Leach h.leach@ieee.org

  • Co-sponsored by SP01, AP/MTT, and School of Computer Sciences and Engineering, FDU
  • Starts 02 October 2018 01:45 PM UTC
  • Ends 09 October 2018 05:45 PM UTC
  • No Admission Charge

  Speakers

Prof. Fred Harris of University of Califronia, San Diego

Topic:

FFT Tutorial and Applied DSP Magic: Cascade Polyphase Filter Banks

Biography:

Professor Harris is at the University of California San Diego where he teaches and conducts research on Digital Signal Processing and Communication Systems. He holds 40 patents on digital receiver and DSP technology and lectures throughout the world on DSP applications. He consults for organizations requiring high performance, cost effective DSP solutions.

He has written some 260 journal and conference papers, the most well-known being his 1978 paper “On the use of Windows for Harmonic Analysis with the Discrete Fourier Transform”. He is the author of the book Multirate Signal Processing for Communication Systems and has contributed to a number of other DSP books.

He was the Technical and General Chair respectively of the 1990 and 1991 Asilomar Conference on Signals, Systems, and Computers, was Technical Chair of the 2003 Software Defined Radio Conference, of the 2006 Wireless Personal Multimedia Conference, of the DSP-2009, DSP-2013 Conferences and of the SDR-WinnComm 2015 Conference. He became a Fellow of the IEEE in 2003, cited for contributions of DSP to communications systems. In 2006 he received the Software Defined Radio Forum’s “Industry Achievement Award”. He was recently notified that in Shanghai, this coming October 2018, he will receive the DSP-2018 conference’s commemorative plaque with the citation: We wish to recognize and pay tribute to fred harris for his pioneering contributions to digital signal processing algorithmic design and implementation, and his visionary and distinguished service to the Signal Processing Community




Agenda

FFT Tutorial: A quick review of the major fast algorithms for computing the DFT: three primary forms, the Cooley-Tukey, the Good-Thomas, and the Winograd. We present a few essential equations and lots of figures and images that show why and how they differ. Which FFT algorithm is in your 4G phone? (Hint: it is not a radix-2 Cooley-Tukey. Why not?) Transforms come in other sizes besides powers of 2. If you have need for a 60 point FFT… don’t zero extend to 64, use the very efficient 60 point FFT: it is more efficient than the 64 point FFT. The eye opening and fun part of the presentation is a number of interesting applications of the FFT that are unrelated to power spectral estimation.

Applied DSP Magic: Cascade Polyphase Filter Banks The polyphaser filter bank comes in two flavors. One does analysis and one does synthesis. These are opposite things. One partitions a broadband input signal into M baseband output signals. The other assembles a broadband output signal from M baseband input signals. What’s impressive is that they each accomplish their tasks with a single filter: not M copies of that filter, but one single filter. The second surprise! They do this counter-intuitive thing: they move spectral bands by aliasing them to and from baseband and then separating the multiple aliases. It seems aliasing is your friend. Have we gotten your attention yet? We then do something silly, to accomplish truly remarkable feats of signal processing, we cascade the analysis and synthesis filter banks. The things we can now accomplish include the formation of variable bandwidth filters without changing filter coefficients at orders of magnitude reduction in processing costs relative to their direct implementation. Convert 3-GHz input data stream into 60 parallel 50 MHz output data streams for processing with reduced cost, lower speed engines. Formation of multiple simultaneous channels with arbitrary bandwidths and center frequencies with similar impressive reductions in processing cost.