Engineering & CS
10 topics
Engineering & CS
Signal processing
Signal processing analyses, transforms, and synthesises signals. The Fourier transform is its central tool and connects it to astrophysics, quantum computing, cryptography, meteorology, and geophysics.
Topics in this field
Adaptive Filtering
Filters that update their coefficients online to minimize a cost function, enabling noise cancellation, echo suppression, and channel equalization.
Compressed Sensing
A framework for recovering sparse signals from far fewer measurements than classical sampling theory requires.
Digital Filter Design
Methods for designing FIR and IIR digital filters to meet prescribed frequency-domain specifications.
Fourier Transform
Decomposing any signal into its constituent frequencies. One of the most powerful tools in all of mathematics.
Kalman Filter
The optimal recursive estimator for linear Gaussian state-space models, fusing predictions with noisy observations.
Matched Filter
The optimal linear filter for detecting a known signal in additive white Gaussian noise, maximizing output signal-to-noise ratio.
Nyquist-Shannon Sampling Theorem
The fundamental theorem establishing the minimum sampling rate required to perfectly reconstruct a bandlimited continuous signal.
Power Spectral Density
Describes how the power of a random signal is distributed across frequencies, estimated via periodogram and spectral averaging methods.
Wavelet Transform
A time-frequency analysis tool that overcomes the fixed resolution of the STFT by using dilated and translated basis functions.
Z-Transform
The discrete-time counterpart to the Laplace transform, enabling algebraic analysis of digital filters and LTI systems.