Adaptive Filtering and Linear Algebra DSP

Recent advances in the computational capabilities of DSP hardware have allowed complex DSP techniques such as equalisation, smart antennas, noise cancellation and MIMO systems to be implemented cost effectively. Adaptive signal processing lies at the core of these DSP techniques. The aim of this course is to educate participants in the theory and applications of digital adaptive filtering algorithms and architectures. The course considers the use of established linear algebra techniques for applications in audio, wireless and mobile communications such as fast equalisation, noise cancellation, beamforming and MIMO systems. A comprehensive description of adaptive filtering algorithms, architectures and applications is provided. This is complemented with case studies in the areas of audio and digital communication.

Content

Linear algebra review
Matrix inversion methods
Adaptive filtering architectures
LMS, RLS, APA and QR algorithms
Adaptive DSP applications
Adaptive filter implementation issues
Audio and digital communication case studies

Audience

The course is suitable for all engineering, technical marketing and technical management staff with previous knowledge of basic DSP concepts.

Event Aim

The aim of this course is to educate participants in the theory and applications of digital adaptive filtering algorithms and architectures. The course considers the use of established linear algebra techniques for applications in audio, wireless and mobile communications such as fast equalisation, noise cancellation, beamforming and MIMO systems. A comprehensive description of adaptive filtering algorithms, architectures and applications is provided. This is complemented with case studies in the areas of audio and digital communication.

On successful completion of the course, attendees will be able to:

Understand basic linear algebra concepts
Be aware of the most common matrix inversion methods available
Apply linear algebra techniques to adaptive filtering
Understand existing adaptive filtering architectures
Gain a good understanding of applications suitable for adaptive filtering
Understand the difference between Least Mean Squares (LMS) and Least Squares (LS) algorithms
Define adaptive algorithm parameters for different applications
Understand implementation limitations and advantages of common adaptive algorithms

Presentation

The course format is: 60% Lectures | 30% Hands-on Labs (simulation based) | 10% Demonstrations

Laboratory Sessions: Professional DSP design software will be used for the laboratory sessions. This advanced software provides a comprehensive and state of the art DSP toolbox for modern signal processing. Steepest Ascent’s adaptive filtering and equalisation simulation libraries will also be used.

Course Materials: All attendees will receive electronic and printed versions of the teaching materials. A DVD containing all the simulation models used during the course will also be distributed. The notes provided form a superset of the materials presented on the course and will allow further in depth study after the course.

Pre-requisites

Prior knowledge of DSP fundamentals (sampling, quantisation, frequency domain analysis, filtering) and bachelor level mathematics is advisable.

Adaptive Filtering and Linear Algebra DSP Syllabus (41.3 kB)

Event Date

on request - Derag Hotel Prinzessin Elisabeth in Munich, Germany www.deraghotels.de

Instructor: Prof. Bob Stewart and team

Prof. Bob Stewart and team Professor Bob Stewart and his team of experienced design engineers from Steepest Ascent of have successfully presented in Europe, United States and Asia. Prof Bob Stewart has extensive experience presenting industry DSP courses in the USA and Europe. He is currently a faculty member of the Department of Electronic and Electrical Engineering at the University of Strathclyde. Prior to joining the University of Strathclyde, Prof Stewart was a visiting professor in Dept of Electrical Engineering at the University of Minnesota in 1990, and a visiting scholar at the University of Southern California in 1986/7. Since 1997 he has been a parttime visiting professor at UCLA.

Prices

1.850,00 € regular fee
1.670,00 € early registration
1.570,00 € per participant of two from the same company
1.480,00 € per participant of three or more from the same company
1.020,00 € University Rate (Please enclose evidence.)

All prices exclude German VAT

Provider

Steepest Ascent

Steepest Ascent has a long history in providing both Public and On-Site courses within the UK, USA and Europe. Through a number of European and US partners Steepest Ascent has delivered a wide range of detailed technical courses to some of the worlds top engineering and academic institutions.

www.steepestascent.com
Contact: Amreet Bhumbra
Phone: +44 141 552 8855
Email: info@steepestascent.com
Ladywell, 94 Duke Street | Glasgow, G4 0UW | United Kingdom

qaqadu event

The qaqadu event gmbh offers professional education with technical training, seminars, and trade shows. In addition to providing and hosting events as technical courses, the MOST(R) Forum, and the automotive roadshow, the Starnberg based specialists in event management also support companies in organizing their events. The offered services reach from the conception and planning through organization and marketing up to the realization of the event.

www.qaqadu.com
Contact: Mandy Ahlendorf
Phone: +49 8151 555009 11
Email: contact@qaqadu.com
Maximilianstrasse 8 | 82319 Starnberg | Germany