Cours offerts (Machines et systèmes intelligents)
- ELG5163 (EACJ5100) Machine Vision (Carleton CRN: 17153)
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Image acquisition. Structured light and stereo ranging. Grey-scale and binary images: geometric and topological properties. Image segmentation, preprocessing, edge finding, processing. Image recognition. Mathematical models for image representation. Morphology. Representation of 3-D objects, scene understanding, motion detection. Massively parallel computer architectures. Machine vision for manufacturing.
- Prerequisites:
- ELG 4153, or the equivalent.
- ELG5124 (EACJ5204) Virtual Environments (Carleton CRN: 17241)
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Basic concepts. Virtual worlds. Hardware and software support. World modeling. Geometric modeling. Light modeling. Kinematic and dynamic models. Other physical modeling modalities. Multi sensor data fusion. Anthropomorphic avatars. Animation: modeling languages, scripts, real-time computer architectures. VE interfaces. Case studies
- ELG5196 (EACJ5709) Neural Networks and Fuzzy Systems (Carleton CRN: 37117)
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Neuro-fuzzy and soft computing. Fuzzy set theory: rules, reasoning and inference systems. Regression and optimization; derivative-based optimization - genetic algorithms, simulated annealing, downhill simplex search.Neural Networks: adaptive networks; bidirectional associative memories; supervised and unsupervised learning; learning from enforcement. Applications: neuro-fuzzy modelling and control, pattern recognition.
- SYSC5001 (ELG6101) Simulation and Modelling (Carleton CRN: 12869)
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Simulation as a problem-solving tool. Random variable generation, general discrete simulation procedure: event table and statistical gathering. Analyses of simulation data: point and interval estimation. Confidence intervals. Overview of modelling, simulation and problem solving using SIMSCRIPT. MODSIM and other languages.
- SYSC5004 (ELG6104) Mathematical Programming for Engineering Applications (Carleton CRN: 33625)
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Introduction to algorithms and computer methods for optimizing complex engineering systems. Includes linear programming, networks, nonlinear programming, integer and mixed-integer programming, genetic algorithms and search methods, and dynamic programming. Emphasizes practical algorithms and computer methods for engineering applications.
- SYSC5401 (ELG6141) Adaptive and Learning Systems (Carleton CRN: 18167)
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System identification. Least squares and recursive identification techniques. Asymptotic and theoretical properties. Model structure selection. Prediction and estimation. Model reference adaptive control and self tuning regulators. Nonlinear adaptive systems. Stability. Neural networks and neuro-control. Applications to robotics, control and pattern recognition.
- Prerequisites:
- SYSC5502, or the equivalent.