"A digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing."
Introduction to DSP architectures, DSP programming, FFT implementation, practical considerations in DSP implementation.
Analog and Digital Signals: Understanding the difference between analog and digital signals paves the way for comprehending digital signal processing.
Sampling and Quantization: A vital digital audio processing concept, sampling refers to taking a snapshot of analog audio signals at specific intervals of time. Quantization, on the other hand, involves assigning numerical values to the signal amplitudes.
Discrete-time Signals and Systems: Discrete signal processing evaluates signals that vary with time, and their responses that are based on differences between how the system interacts to the signal input.
Fourier Analysis: An essential topic in digital signal processing, Fourier analysis helps in understanding how be can break waveforms into different frequencies.
Time and Frequency Domain Analysis: The time domain displays the sound signal's amplitude versus time, while the frequency domain shows the energy of each frequency component present in the sound signal.
Z-transform and The Laplace Transform: The Z-transform, a fundamental concept in digital signal processing, helps in analyzing discrete-time systems; while the Laplace Transform helps in examining continuous-time linear systems.
Filters: A crucial building block in analog and digital signal processing, filters are essential in removing unwanted noise from the input signals.
Fast Fourier Transform (FFT): An efficient algorithm for performing discrete Fourier transforms, FFT is useful for digital signal-processing applications.
Convolution: A mathematical technique used in digital signal processing to analyze the behavior of systems and signals.
Digital Signal Processors and their Applications: DSPs are specialized microprocessors, and one of their primary functions is processing signals, amplifying or filtering them.
Discrete Wavelet Transforms (DWT): An analytical tool applied in signal processing, DWT helps to reduce noise, detect edges and evaluate signals that contain noises or spikes.
Adaptive Filter Theory: This topic in digital signal processing covers the algorithms and methods used to streamline signals, suppress noise, and remove distortions.
Time-Frequency Signal Analysis: This analysis method is used in digital signal processing to analyze signals that have changing frequency characteristics over time. It builds a representation of the signal frequency over time.
Speech Processing: One of the major fields of application for digital signal processing, speech processing includes speech recognition, voice synthesis, and signal compression.
Image Processing: The study of processing digital images using various signal processing techniques.
Digital Modulation: The alteration of radio signals to convey digital data, applying a digital modulation scheme to an analog communication channel converts digital signals into analog signals that can be transmitted via radio waves.
Error Correction Codes: Error correction codes helps in minimizing random errors in digital communication, using various schemes like Hamming, Reed-Solomon, Viterbi and others.
Digital Signal Processing Applications: Real-world applications of digital signal processing, which include medical imaging and diagnosis, audio, video and image processing and compression, telecommunications and network communications, and aerospace applications.
Fixed-point DSPs: These DSPs are designed to perform arithmetic operations on integers and fixed-point numbers.
Floating-point DSPs: These DSPs are designed to perform arithmetic operations on floating-point numbers.
Hybrid DSPs: These DSPs are a combination of fixed-point and floating-point DSPs, and they can be configured to operate in either mode.
General-purpose DSPs: These DSPs are designed for a wide range of signal processing applications, including audio and video processing, telecommunications, and image processing.
Application-specific DSPs: These DSPs are designed for specific applications such as motor control, voice recognition, and wireless communication.
Multi-core DSPs: These DSPs have multiple processing cores, which allow them to handle multiple tasks simultaneously.
Vector processors: These DSPs are designed to perform vector computations, which involve manipulating arrays of data.
Graphics processing units (GPUs): These DSPs are designed for multimedia applications, such as gaming, video playback, and image processing.
Digital signal controllers (DSCs): These are DSPs that have additional hardware for control tasks, such as motor control or power conversion.
"DSPs are fabricated on MOS integrated circuit chips."
"They are widely used in audio signal processing, telecommunications, digital image processing, radar, sonar and speech recognition systems..."
"...and in common consumer electronic devices such as mobile phones, disk drives, and high-definition television (HDTV) products."
"The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals."
"Most general-purpose microprocessors can also execute digital signal processing algorithms successfully..."
"...but may not be able to keep up with such processing continuously in real-time."
"...dedicated DSPs usually have better power efficiency, thus they are more suitable in portable devices such as mobile phones because of power consumption constraints."
"DSPs often use special memory architectures..."
"...that are able to fetch multiple data or instructions at the same time."
"...used in audio signal processing..."
"...used in telecommunications..."
"...used in digital image processing..."
"...used in radar, sonar..."
"...speech recognition systems..."
"...more suitable in portable devices such as mobile phones because of power consumption constraints."
"...dedicated DSPs usually have better power efficiency..."
"...because of power consumption constraints."
"DSPs are fabricated on MOS integrated circuit chips."
"The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals."