Digital Signal Processing -- Practical Techniques, Tips and Tricks

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Digital Signal Processing -- Practical Techniques, Tips and Tricks

3-Day Course

$2095 per person

Summary

The goal of this 3-day course is to Introduce, explain, and demonstrate powerful, proven techniques, tips and “tricks of the trade” that can dramatically improve accuracy, speed and efficiency in Digital Signal Processing (DSP) applications.

The concepts are first presented using many colorful, clear figures along with plain English explanations and real-world examples. They are next demonstrated using clearly written MATLAB programs (with graphics). This way the student sees the key equations “in action” which increases intuitive understanding and learning speed. These (free) working programs can also be later modified or adapted by the student for customized, site specific use.

Each student will receive extensive course slides, a CD with MATLAB m-files for demonstration and later adaptation, supplementary materials and references to aid in the understanding and application of these “techniques, tips, and tricks” and a copy of the instructor’s latest book “The Essential Guide to Digital Signal Processing”.

NOTE: A laptop is convenient to see course materials in color but is NOT a requirement for this course.

This course can also be delivered as live synchronous learning

View Course Sampler

  • How to recognize and avoid common DSP pitfalls through an increased, intuitive understanding of Sampling, Fourier Transforms, Filtering, Convolution, and Correlation.
  • How to understand and implement advanced DSP applications such as Cross Ambiguity Functions (CAFs), Stochastic Resonance, and Processing Gain to coax extremely weak signals above the detection threshold.
  • How to understand and work with the latest Communications Technology (5-G, LTE, OFDMA) using familiar DSP methods.
  • How to understand and utilize additional clever “Tricks of the Trade” not found in most math-based textbooks or classes.
  • How to confidently (and correctly) use more advanced DSP techniques such as Optimal and Matched Filtering, Hilbert Transforms, Multirate Systems, Multiresolution, and Time/Frequency methods (including STFTs and Wavelets).

This course is vastly different from the typical Applied Mathematics DSP courses in that it is an in-depth, comprehensive treatment but from a more intuitive, understandable perspective. This approach de-mystifies, clarifies, and demonstrates the techniques thus allowing the student to quickly learn and correctly apply them.

  1. New insights and applications of traditional DSP. How to avoid common mistakes and traps when converting analog signals to digital. The underutilized power of Median Filtering in Edge Detection. Employing Matched Filtering to pull out a weak signal even if it has been stretched/shifted. Signal Averaging in time, frequency, and phase for cleaner results. Tradeoffs in Windowing. Innovative uses of Autocorrelation and Cross-correlation for Processing Gain.

  2. Exploiting the capabilities of Complex Signals. Time, Frequency, and Phase together in workable formats. Edge detection. Signal Envelopes. Using a Hilbert Transform to precisely shift the frequency of a real signal. Creating an essentially Ideal Filter with minimal or zero bin leakage.

  3. Multirate, Multresolution, Time/Frequency, and Wavelets. Compression and De-Noising. Advanced interpolation. Short Time Fourier Transforms. Re-sampling to line up signals for coherent processing. Wavelet Transforms that tell you the time, the frequency and even the shape of pulses, blips, or other “events” in your signal. Example of how to recover a signal swamped in noise (10,000x). Alias Cancelling Filters. Continuous and Discrete Wavelet Transforms with examples.

  4. DSP Techniques. How to extract a signal from heavy noise using Cross Ambiguity Functions (CAFs). Precision Peak Interpolation. Stein’s Method. Dithering and Stochastic Resonance–how to inject noise to actually improve the result. Harmonics and Intermodulation Distortion–ways to deal with strong false signals at frequencies very close to your signal of interest.

  5. Applications of DSP in Communications.How to understand and implement Orthogonal Frequency Division Multiple Access (OFDMA) using surprisingly familiar DSP techniques (IFFT then FFT). DSP usage in Advanced Communications Multiple Access Schemes. Intuitive comparisons of FDMA, TDMA, CDMA, OFDMA and SDMA.

  6. Skewed Distributions in Statistical Signal Processing. How to work with real-world distributions such as Lognormal, Rayleigh, Chi-Square and other non-Gaussian representations (real-life data seldom lies on a strict Bell Curve).

  7. Additional Practical DSP Tips and Tricks. A sliding DFT that computes selected results orders of magnitude faster than the FFT. Extremely efficient minimization using a Downhill Simplex “amoeba”. How to better utilize Symbolic Math. Other selected state-of-the-art techniques. Application of above “techniques, tips, & tricks” to DSP areas with strong market growth: communications, A/V, space, medical, defense, oil & gas exploration, financial and other critical fields.

  8. Workshop on Student-Requested Challenges. Help, advice, and counsel by instructor on technical problems brought by students to this class
  • How to recognize and avoid common DSP pitfalls through an increased, intuitive understanding of Sampling, Fourier Transforms, Filtering, Convolution, and Correlation.
  • How to understand and implement advanced DSP applications such as Cross Ambiguity Functions (CAFs), Stochastic Resonance, and Processing Gain to coax extremely weak signals above the detection threshold.
  • How to understand and work with the latest Communications Technology (5-G, LTE, OFDMA) using familiar DSP methods.
  • How to understand and utilize additional clever “Tricks of the Trade” not found in most math-based textbooks or classes.
  • How to confidently (and correctly) use more advanced DSP techniques such as Optimal and Matched Filtering, Hilbert Transforms, Multirate Systems, Multiresolution, and Time/Frequency methods (including STFTs and Wavelets).

This course is vastly different from the typical Applied Mathematics DSP courses in that it is an in-depth, comprehensive treatment but from a more intuitive, understandable perspective. This approach de-mystifies, clarifies, and demonstrates the techniques thus allowing the student to quickly learn and correctly apply them.

Tuition for this three-day course is $2095 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to ATI@ATIcourses.com.

Instructor

Dr. Lee Fugal is President of S&ST Technical Consulting–providing guidance and solutions since 1991. He holds a Masters in Applied Physics (DSP) and is Chairman of the San Diego IEEE Signal Processing Society. He is the author of “Conceptual Wavelets in Digital Signal Processing” and co-author with Richard Lyons of “The Essential Guide to Digital Signal Processing”. Drawing on more than 40 years of industry experience, Lee teaches upper-division university courses in DSP and short courses for working engineers at various venues around the country. An IEEE Senior Member, he is a recipient of the IEEE Third Millennium Medal.


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