Covers examples of signal processing, analog signal processing, continuous amplitude modulation, image processing, compression, micro-systems, and medical electronics.
Covers the properties of the Discrete-Time Fourier Transform, including linearity, shifts, time reversal, differentiation, convolution, conjugate symmetry, and Parseval's Relation.
Introduces convolutional neural networks for image processing, covering basic components, architectures, and practical applications, including denoising and segmentation.
