EE363
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Linear Dynamical Systems
Course Description
State-space representation of linear dynamical systems. Eigenvalues of non-symmetric matrices. Left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input/multi-output systems, impulse and step matrices. Convolution and transfer-matrix descriptions. Control, reachability, and state transfer. Observability and least-squares state estimation. Positive systems and Perron-Frobenius theory. Response of linear dynamical systems to Gaussian random inputs. The linear-quadratic regulator and the Kalman filter. Applications from a broad range of disciplines including circuits, signal processing, machine learning, and control systems.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Programs
EE363
is a
completion requirement
for:
- (from the following course set: )
- (from the following course set: )