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Joint Chapter of Signal Processing, Oceanic Engineering, and Geoscience and Remote Sensing

Past Events

·        Multi-Processor SoC's: Trends and Technologies, Dr. Pierre G. Paulin

 

·        Position Estimation Using Non-Linear Transformation of Measurements, Dr.  Rajamani Doraiswami

 

·        A Robust Hybrid Intelligent Position/Force Control Scheme for Cooperative Manipulators, Dr. Wail Gueaieb

 

·        Backward Compatible Wideband Voice over Narrowband Low-   Resolution Media by Dr. Heping Ding

 

·        Face recognition in video as a new biometrics modality and the appropriate associative memory framework by Dr. Dmitry O. Gorodnichy

 

·        Theory and implementation of particle filters by Dr. Miodrag Bolic

 

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Multi-Processor SoC's: Trends and Technologies

Slides

 

Speaker : Pierre G. Paulin, Ph.D.
Director, SoC Platform Automation
Advanced System Technology
STMicroelectronics Inc.,
Ottawa, Canada

 

 

Place:   Room, 5084, School of Information Technology and Engineering,

University of Ottawa,

800 King Edward,
Ottawa, Ontario, Canada, K1N 6N5

Date: February 6th at 6:15pm

Organization: IEEE Joint Chapter of Signal Processing, Oceanic Engineering, and Geoscience and Remote Sensing Ottawa Chapter together with IEEE Computer Society Ottawa Chapter


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Abstract:
This presentation will address emerging needs in system-level prototyping for complex multi-processor SoC platforms, based on our experience with STMicroelectronics' platforms in consumer-oriented multimedia applications.

 

We will introduce first elements of solutions developed at ST to address these needs. We present our MultiFlex toolset which maps high-level parallel programming models onto heterogeneous parallel H/W and S/W resources. Results for a mobile multimedia platform application are summarized.

 

Bio:
Pierre Paulin is director of System-on-Chip Platform Automation at STMicroelectronics, Ottawa, Canada. Previously, he was director of Embedded Systems Technologies for ST in Grenoble, France. Before this, he managed embedded software tools and high-level synthesis R&D with Nortel Networks research labs. His interests are in design automation technologies for multi-processor systems, embedded systems and system-level design. He obtained a Ph.D. from Carleton University, Ottawa, in 1988, and B.Sc. and M.Sc. degrees from Laval University, Quebec in 1982 and 1984 respectively. He won the best presentation award at DAC in 1986, and won the best paper award at ISSS-Codes in 2005.

 

 

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Position Estimation Using Non-Linear Transformation of Measurements

Speaker Prof. Rajamani Doraiswami, Department of Electrical and Computer Engineering, The University of New Brunswick, Fredericton, New Brunswick Canada.

Date:           January 13, 2006
Time:           15:00-16:00
Location:       Room 5084 of SITE Building at the University of Ottawa

 

A novel Kalman filter­-based scheme is proposed to estimate the navigational states of a vehicle from the range measurements obtained using beacons (transmitter-receivers): at least three placed at known locations and one on the vehicle. The novelty of the scheme stems from

    • The use of pseudo­measurements which are some non-linear function of the range measurements (pair-wise sums and differences in the square of ranges) so that the measurement model is linear with the resulting Kalman filter globally convergent
    • The optimal location of the beacons to ensure that the state estimation error is minimized, resulting in the estimation accuracy being linear in the true states.

The proposed scheme is evaluated on a number of examples.

About the speaker:

R.Doraiswami ( M'76-SM '85) obtained his B.E. from Victoria Jubilee Technical Institute, Bombay, India, M.E. from the Indian Institute of Science, Bangalore, India and Ph.D from Johns Hopkins University, Baltimore, USA  all in  Electrical Engineering, in 1962, 1965 and 1971 respectively.

He was a Professor of Electrical Engineering at the Federal University of Santa Catarina, Florianopolis, Santa Catarina, Brazil from 1971to 1981, and at the Federal  University of Rio de Janeiro, Rio de Janeiro, Brazil from 1976-1978. Since 1981 he has been with the University of New Brunswick, Fredericton, New Brunswick, Canada where he is currently a professor of electrical and computer engineering. He has held visiting positions at various universities in Netherlands, Germany, Singapore and China. He was consultant to industries including Siemens, Lockheed Martin, Biopeak, Lizzottem consultants, and GKN helicopter.   He was a United Nations expert in India.

His area of research include control system, power system, signal processing, detection and estimation, navigation, and pattern recognition, biomedical application. He is a senior member of the IEEE, fellow of the Indian Institute of Engineers and a Professional Engineer in the Province of New Brunswick, Canada.

 

 

 


A Robust Hybrid Intelligent Position/Force Control Scheme for Cooperative Manipulators


Speaker:        Dr Wail Gueaieb, Assistant professor, SITE
Date:           Thursday April 21, 2005
Time:           17:00-18:30
Location:       Room 5084 of SITE Building at the University of Ottawa

 

Abstract

 

A decentralized adaptive fuzzy controller is proposed for addressing the problem of controlling the positions and internal forces within multiple coordinated manipulator systems in the face of parametric and modeling uncertainties as well as external disturbances. The controller makes use of a multi-input multi-output fuzzy logic engine and a systematic online adaptation mechanism to fully approximate the overall system's dynamics. Unlike conventional adaptive controllers, the proposed controller does not require a perfect prior model of the system's dynamics nor does it require a linear parameterization of the system's uncertain physical parameters. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying intensity levels of the aforementioned uncertainties, and the position and the internal forces are proven to asymptotically converge to zero under such conditions. Through a computer simulation of two 3-DOF manipulators, the performance of the controller is verified and compared to that of one of the most efficient conventional adaptive controllers proposed in the literature.

 

Biography

 

Dr. Wail Gueaieb received the Bachelor and Master’s degrees in Computer Engineering and Information Science from Bilkent University, Turkey, in 1995 and 1997, respectively, and the Ph.D. in Intelligent Mechatronics from the University of Waterloo, Canada, in 2001. He then joined Intelligent Mechatronic Systems Inc. in 2001 where he held the positions of a senior systems design engineer in expert systems and a software manager. During his career at Intelligent Mechatronic Systems Inc., he worked on the design, implementation, and productization of a new generation of smart advanced automotive safety systems. He is also the author/co-author of three patents. In July 2004, he joined the School of Information Technology and Information Science (SITE). His areas of expertise span the fields of intelligent systems design using tools of computational intelligence with application to a wide range of industries.

 

 

 

 


Title:         Backward Compatible Wideband Voice over Narrowband Low-   Resolution Media

Speaker:       Dr. Heping Ding

Time:          Monday, February 14th, from 16:30 to 18:00

Place:         Room 5084, SITE, University of Ottawa, 800 King Edward, Ottawa

 

This presentation discusses a scheme for transmitting or storing a wideband (up to 7 kHz) voice in a narrowband (up to 3.4 kHz) channel or medium with a low resolution (G.711, 8-bit) data format. The scheme is fully backward compatible; a conventional receiver, without any decoding mechanism, can still access a narrowband version of the wideband voice. The proposed scheme can be applied where a high quality wideband voice is needed but the physical capacity is limited. Examples are voice-over-IP, digital private branch exchange, as well as storage and playback. An audio demonstration will be given.

 

 

Dr. Heping Ding joined Acoustics and Signal Processing Group, Institute for Microstructural Sciences, National Research Council, Canada, in 2001, where he is holding the position of Senior Research Officer. He has also served in BNR/Nortel, Canada, as a Senior Audio Signal Processing Specialist. Since 2003, Dr. Ding has been an Adjunct Professor with the School of Information Technology and Engineering (SITE) at the University of Ottawa, Canada, and an Adjunct Professor at the School of Graduate Studies, Ryerson University, Canada. Also as a part-time professor at SITE, University of Ottawa, he has taught digital signal processing courses at graduate and 4th year levels. So far, Dr. Ding holds 10 issued patents and 39 open and confidential major publications in fields of subjective audio, telephony, adaptive filtering, echo control, non-stationary signal processing, noise reduction, audio coding, and electronic equipment. In addition, he has received more than 13 awards from industry, universities, and science and technology communities. Dr. Ding is a Senior Member of IEEE.

 

 

 

 


Title: Face recognition in video as a new biometrics modality and the appropriate associative memory framework

Date: Wednesday, December 15, 2004

Time: 16:00-17:30

Location: Room 5084 of SITE Building at the University of Ottawa

Speaker: Dr. Dmitry O. Gorodnichy, Research Officer

  NRC-CNRC Institute for Information Technology

  Computational Video Group

  http://iit-iti.nrc-cnrc.gc.ca

  http://synapse.vit.iit.nrc.ca (project homepage)

 

Abstract

 

The purpose of this talk is two-fold. First, the audience will be introduced with the basics of the attractor-based associative neural networks. These networks are known as a mathematical tool for building recognition systems which work in a fashion similar to that of the human brain. Second, the audience will be presented with a new framework for recognizing faces in video. While the problem of recognizing faces in video has received a lot of attention recently, in particular, because of such a highly demanded application of it as security surveillance, this problem is often erroneously treated as an extension of the problem of recognizing faces in photographs.

Photographs, which are usually taken under very constrained conditions, provide hard biometrics data, as do, for instance, the fingerprints. Video footage, on the other hand, such as the one taken by a surveillance camera, will very unlikely contain the facial data of high quality and is therefore the source of "softer" biometrics. As we will show, however, the soft biometrics provided by video is still very informative and can be efficiently used to memorize and recognize faces. In the demonstrations to be shown, the developed mini brain model allows one to discriminate guests of a talk show in a prerecorded low-resolution video.

 

 

Speaker Bio

Dr. Dmitry Gorodnichy is a research officer with the Computational Video Group of the Institute for Information Technology of the National Research Council of Canada. He has two Ph.D. degrees: one - in Computing Science (2000) from the University of Alberta, Edmonton, Canada, for his work on Vision-based World Model Learning, and the other (1997) - in Mathematics from the Glushkov Cybernetics Center of Ukrainian Ac.Sc., Kiev, Ukraine, for his work on Mathematical models of human memory. His MSc (with honours) in Information Technology (1994) is from the Moscow Institute of Physics and Technology, Moscow, Russia. He is the author of two patents and over thirty conference and journal papers, including an IJCNN Best Presentation Award paper, a recipient of several scientific awards, including the Young Investigator Award from the Canadian Image Processing and Pattern Recognition Society and the NRC-CNRC Outstanding Scientific Achievement Award. He is the principle investigator of Nouse™ (Nose as Mouse) and Blink Detection perceptual vision technologies featured in the 2002 and 2003 NRC-CNRC Annual Reports, and is listed as one of

2003 Leaders of Tomorrow by the Partnership Group for Science and Engineering of Canada. He was the Program Chair for the International Conference on Vision Interface, the organizer and the program chair of the First IEEE Workshop on Face Processing in Video and is now the Exhibits Chair for the INNS-IEEE International Joint Conference on Neural Networks to be held in Montreal next year. He is a reviewer for many scientific conferences, journals and organizations, including NSERC, and is also presently the Chair for IEEE Computational Intelligence Society, Ottawa Chapter.

 

 

 


Title:         Theory and implementation of particle filters

Speaker:       Dr. Miodrag Bolic

Time:          Friday November 12, 2004, 11 a.m.,

Place:         Room 5084, SITE, University of Ottawa, 800 King Edward, Ottawa

 

Abstract: 

In recent years particle filters have attracted great attention in several research communities. These filters are used in problems where the interest is in tracking and/or detection of dynamic signals. The standard solutions of such problems in many applications are based on the Kalman filters or extended Kalman filters. In situations when the problems are nonlinear or the noise that distorts the signals is non-Gaussian, the Kalman filters

provide solution that may be far from optimal. The particle filters are an intriguing alternative to the Kalman filters due to their excellent performance in very difficult problems. The focus of this presentation will be on the principles of particle filtering. This presentation will also address applications of particle filters and the problems that arise in the hardware implementation of particle filters as well as the approaches to resolve them.

 

 

 


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