Development of Statistical Signal Processing Algorithms Training
Commitment | 3 Days, 7-8 hours a day. |
Language | English |
User Ratings | Average User Rating 4.8 See what learners said |
Price | REQUEST |
Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
Development of Statistical Signal Processing Algorithms Training covers the fundamental approaches to developing statistical signal processing algorithms to meet system design specifications. Additionally, the algorithms that are currently used in practice and have stood the “test of time” are highlighted. The methodology to design, evaluate, and test new algorithms is presented in a simple step-by-step manner. In doing so, the computer language MATLAB is utilized. All algorithms and methods discussed have been implemented in MATLAB and will be provided to the attendee. The Development of Statistical Signal Processing Algorithms Training course is designed for engineers, scientists, and other persons who wish to implement and/or design statistical signal processing algorithms without having to scour the current literature for possible solutions.
The presentations will emphasize actual working algorithms and will de-emphasize the mathematics behind them so that the course will be accessible to those who may not be familiar with the theoretical foundations. Knowledge of the instructor’s previous books, “Modern Spectral Estimation”, “Fundamentals of Statistical Signal Processing: Estimation” and “Fundamentals of Statistical Signal Processing: Detection” is not required. Attendees are encouraged to bring their laptops so that they are able to exercise the programs along with the instructor. All MATLAB source codes will be provided for the course and future use. Each participant will receive the recently released book “Fundamentals of Statistical Signal Processing, Vol. III, Practical Algorithm Development”, by Steven Kay, Prentice-Hall, 2013. The book contains a CD with MATLAB programs.
WHAT'S INCLUDED?
- 3 days of Development of Statistical Signal Processing Algorithms Training with an expert instructor
- Development of Statistical Signal Processing Algorithms Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- Development of Statistical Signal Processing Algorithms – https://www.wiley.com/
- Development of Statistical Signal Processing Algorithms – https://www.packtpub.com/
- Development of Statistical Signal Processing Algorithms – https://store.logicaloperations.com/
- Development of Statistical Signal Processing Algorithms Training – https://us.artechhouse.com/
- Development of Statistical Signal Processing Algorithms – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completing this Development of Statistical Signal Processing Algorithms Training course, learners will be able to meet these objectives:
- A step-by-step approach to the design of algorithms
- Comparing and choosing signal and noise models
- Performance evaluation, metrics, tradeoffs, testing, and documentation
- Optimal approaches using the ‘big theorems”
- Algorithms for estimation, detection, and spectral estimation
- Lessons learned and “rules of thumb” for each topic
- Complete case studies
CUSTOMIZE IT
- We can adapt this Development of Statistical Signal Processing Algorithms Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Development of Statistical Signal Processing Algorithms course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Development of Statistical Signal Processing Algorithms course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the Development of Statistical Signal Processing Algorithms course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this Development of Statistical Signal Processing Algorithms course:
- All
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this Development of Statistical Signal Processing Algorithms course are:
- N/A
COURSE SYLLABUS
Development of Statistical Signal Processing Algorithms Training
- Methodology for algorithm design: flow charts, an example of algorithm design
- Mathematical modeling of signals: linear vs. nonlinear, deterministic signals, random signals, unknown parameters
- Mathematical modeling of noise: white Gaussian noise, colored Gaussian noise, general Gaussian noise, IID non-Gaussian noise
- Signal model selection: flow charts, random processes, transients, periodic models, model order estimation
- Noise model selection: flow charts, estimation of probability density functions, spectrum, moments, covariance matrix, model order estimation, confidence intervals
- Performance, evaluation, and testing: metrics, Monte Carlo evaluations, bias versus variance, mean square error, probability of error, receiver operating characteristics, software development, documentation
- An optimal approach using the big theorems: Neyman-Pearson, likelihood ratio, maximum likelihood, maximum a posterior, minimum MSE, linear models
- Specific algorithms for estimation, detection, and spectral estimation: parameter estimation, signal extraction, adaptive filtering, sinusoidal estimation, matched filters, estimator-correlator, spectral estimation via Fourier and high-resolution methods
- Complex data extensions: complex demodulation, complex random variables, and random processes, extensions of all algorithms to complex data
- Case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring