"Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations."
The processing of signals (such as audio or video) using mathematical techniques to reduce noise, compress data, or extract features.
Signals and Systems: Introduction to continuous and discrete-time signals and systems, Impulse response, Convolution, Fourier series, Fourier transform, sampling theorem, and z-transform.
Digital Filter Design: Introduction to FIR and IIR filters, impulse response, frequency response, design methods such as windowing, frequency sampling, and filter transformation.
Discrete Fourier Transform: Mathematical foundation of DFT, the relationship between DFT and FFT, applications of DFT in speech processing and image processing.
Image and Video Processing: Image enhancement, restoration, transformation, compression, and segmentation, introduction to video processing including motion estimation and video compression techniques.
Speech Processing and Recognition: Speech analysis, synthesis, coding, and recognition, applications in speech-based human-machine interaction and automatic speech recognition systems.
Wavelets: Introduction to wavelet transform, wavelet analysis, wavelet packets, and applications of wavelets in speech and image processing.
Adaptive Signal Processing: Adaptive filters, LMS algorithm, RLS algorithm, and applications in noise cancellation, system identification, and channel equalization.
Digital Signal Processors: Introduction to DSP architectures, DSP programming, FFT implementation, practical considerations in DSP implementation.
"The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."
"The application of digital computation to signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."
"DSP can involve linear or nonlinear operations. Nonlinear signal processing is closely related to nonlinear system identification and can be implemented in the time, frequency, and spatio-temporal domains."
"In digital electronics, a digital signal is represented as a pulse train, which is typically generated by the switching of a transistor."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."
"DSP is applicable to both streaming data and static (stored) data."
"Nonlinear signal processing is closely related to nonlinear system identification and can be implemented in the time, frequency, and spatio-temporal domains."
"The application of digital computation to signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression."
"In digital electronics, a digital signal is represented as a pulse train, which is typically generated by the switching of a transistor."
"DSP is also fundamental to digital technology, such as digital telecommunication and wireless communications."
"DSP applications include audio and speech processing, signal processing for telecommunications, control systems, and wireless communications."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."
"The application of digital computation to signal processing allows for many advantages over analog processing in many applications, such as error detection and correction in transmission as well as data compression."
"Nonlinear signal processing is closely related to nonlinear system identification and can be implemented in the time, frequency, and spatio-temporal domains."
"DSP applications include digital image processing, data compression, video coding, audio coding, and image compression."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."
"DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others."