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Course Criteria
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4.00 Credits
In this course students are introduced to MIMO systems and their designs using state space techniques. Linear algebra: Vectors, linear independent of vectors, vector space and null space, rank of a matrix eigen values and eigen vectors, transformation of matrices, functions of matrices, matrix polynomials, Cayley Hamilton theorem state space formulations, canonical forms, controllability and observability, relations between state space and transfer function models, solution of state equations, state space design (pole placement), comparison with conventional design, and introduction to other forms of state space designs. (0301-514) Class 4, Credit 4
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3.00 Credits
Studies the theory and design of microwave components and circuits. Reviews basic EM theory, TEM waves in transmission lines, TE and TM waves in rectangular waveguides, microstriplines and striplines, TE and TM waves in cylindrical waveguides, the scattering matrix description of multiport microwave circuits, waveguide tees, directional couplers and phase shifters, microwave integrated circuit components-branchline couplers, power dividers, hybrid ring couplers and phase shifters, rectangular, cylindrical and coaxial cavity resonators, waveguide and coaxial line fi lters and waveguide frequency meters, microwave integrated circuit high pass and band pass fi lters, ferrite components. Laboratory illustrates various microwave component design and measurement techniques. Class 3, Lab 3, Credit 4 (W)
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3.00 Credits
Study of fundamental principles of electronic instrumentation and design consideration associated with biomedical measurements and monitoring. Topics to be covered include biomedical signals and transducer principles, instrumentation system fundamentals and electrical safety considerations, amplifi er circuits and design for analog signal processing and conditioning of physiological voltages and currents as well as basic data conversion and processing technology. Laboratory experiments involving instrumentation circuit design and test will be conducted. (0301-382, 482, 554) Class 4, Lab 3, Credit 4 (W)
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3.00 Credits
Biological entities probably represent one of the most diffi cult environments in which to obtain or generate accurate and reliable signals. This course will discuss the techniques, mechanisms and methods necessary to transfer accurate and reliable information or signals with a biological target. Various biomedical sensor and transducer types including their characteristics, advantages, disadvantages and fabrication will be covered. Discussions will include the challenges associated with providing a reliable and reproducible interface to a biological entity, the nature and characteristics of the associated signals, the types of applicable sensors and transducers and the circuitry necessary to drive them. (0301-382, 482) Class 4, Lab 3, Credit 4
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3.00 Credits
Investigation and study of the concepts and underlying mechanisms associated with electrical signals in mammalian biology and physiology with a signifi cant emphasis on methods, techniques and understanding of electrical potential distribution and current fl ow derived from circuit analysis. Intended to provide engineers with insight into the relationship between the study of electricity and its applicability to a wide variety of physiological mechanisms ranging from intracellular communication and control to cognitive function and bodily movement. Successful completion of the course will require generation of a signifi cantly in-depth analysis report on some electrophysiological phenomenon or mechanism. (0301-381, 1026-365) Class 4, Lab 3, Credit 4 (F)
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4.00 Credits
Discussion and study of the methods and techniques that may be optimally employed for the fi xed and adaptive processing of information with biological and physiological origin. The challenges and unique features of these types of signals will be discussed and application of known signal processing techniques that accommodate linear, non-linear and stochastic signals for the purpose of analysis, detection and estimation, monitoring and control will be studied. Successful participation in the course will entail completion of at least one project involving incorporation of these techniques in a biomedical application. (Permission of instructor or graduate standing) Class 4, Credit 4
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4.00 Credits
Cybernetics refers to the science of communication and control theory that is concerned especially with the comparative study of automatic control systems (as in the nervous system and brain and mechanical-electrical communications systems. This course will present material related to the study of cybernetics as well as the aspects of robotics and controls associated with applications of a biological nature. Topics will also include the study of various paradigms and computational methods that can be utilized to achieve the successful integration of robotic mechanisms in a biological setting. Successful participation in the course will entail completion of at least one project involving incorporation of these techniques in a biomedical application. (Permission of instructor or graduate standing) Class 4, Credit 4
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4.00 Credits
Application of control system principles associated with input-output analysis, steady state and transient response, feedback concepts, system identifi cation and simulation to the study of physiological processes involved in the regulation and maintenance of homeostasis in a human being. Among areas of interest are coordinated movement, vision, cardiovascular response, fl uid management and metabolism. (0301-514 and permission of instructor) Class 4, Credit 4
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3.00 Credits
The study of a variety of semiconductor devices generally used for purposes other than signal processing, including thyristors, unijunction transistors, opto-couplers, power MOS and IGBTs. Applications stressed are concerned with the use of electrical power for control of lighting, motion and heat. Particular attention is given to calculating power dissipation, heat sinks and thermal management. (0301-545) Class 3, Lab 3, Credit 4
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4.00 Credits
The course will start with the history of artifi cial intelligence and its development over the years. This course will explore a variety of artifi cial intelligence techniques, and their applications and limitations. Some of the AI techniques to be covered in this course are intelligent agents, problem-solving, knowledge and reasoning, uncertainty, decision making, learning (Neural networks and Bayesian networks), reinforcement learning, swarm intelligence, Genetic algorithms, particle swarm optimization, applications in robotics, controls, and communications. Students are expected to have any of the following programming skills: C/C++, MATLAB, Java, or any other high level programming language. Class 4, Credit 4
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