Comprehensive introduction to analysis of continuous and discrete-time signals and systems. Linear time-invariant systems, convolution; Fourier series representations of periodic signals; Continuous ...

It covers the solving of convolution integrals and differential equations, the transformation of signals to Fourier series, the Fourier and Laplace transforms, with their application, in continuous ...

Topics: linear time-invariant systems Fourier, Laplace, and Z-transforms system stability and design signal analysis sampling and modulation (possibly) wavelet transforms and principle component ...

A major focus of the course is the Fourier transform — how, when, and why to use it. We also study linear time-invariant systems, modulation, quantization, and stability (using the related Laplace ...

Transform-based algorithms have wide applications in applied probability, but rarely provide computable error bounds to guarantee the accuracy. We propose an inversion algorithm for two-sided Laplace ...