Psychoacoustics and Signal Processing

Related lectures (30)

Page 2 of 3

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.

Covers Fourier transform, sampling, reconstruction, Nyquist frequency, and ideal signal reconstruction.

Explains the basics of Fourier transform and demonstrates its application through examples, including periodic functions and Fourier Transform Pairs.

Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.

Explores the Discrete Fourier Transform applied to signals of unlimited duration using various windows for improved accuracy.

Explores discrete Fourier transform, signal reconstruction, sampling interpretation, and periodic signal repetition.

Covers the concepts of quantization, coding, and sampling in signal processing.

Explores Fourier series, DFT, FFT, and their applications in signal processing and spectroscopy.

Covers the basics of signal processing, including Fourier transform, linear systems, and signal manipulation.

Covers the basics of the Fourier transform and its applications in signal processing.