IT Workshop (Sci Lab/MATLAB) | 13. Real-Time Signal Processing using MATLAB by Abraham | Learn Smarter
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13. Real-Time Signal Processing using MATLAB

Real-time signal processing is vital in various modern applications, from communications to biomedical instruments. MATLAB offers robust tools for developing and simulating these systems, enabling rapid modeling and testing. The chapter covers fundamental concepts, practical example implementations, and challenges in real-time processing, emphasizing MATLAB's capabilities.

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Sections

  • 13

    Real-Time Signal Processing Using Matlab

    This section covers the principles and implementation of real-time signal processing using MATLAB, showcasing its toolbox capabilities for various applications.

    Learning Practice

  • 13.1

    Basics Of Signal Processing

    This section introduces the fundamental concepts of signal processing, including definitions, classifications, and types of signal processing systems.

    Learning Practice

  • 13.1.1

    Definition Of A Signal

    A signal is a function that conveys information about a phenomenon, which can be time-varying or spatially-varying.

    Learning Practice

  • 13.1.2

    Classification Of Signals

    This section discusses the various types of signals classified based on their characteristics, such as continuous-time, discrete-time, deterministic, random, periodic, aperiodic, energy, and power signals.

    Learning Practice

  • 13.1.3

    Signal Processing Systems

    This section provides an overview of the different types of signal processing systems, emphasizing analog and digital processing and distinguishing between real-time and offline processing.

    Learning Practice

  • 13.2

    Real-Time Signal Processing Concepts

    This section introduces key concepts in real-time signal processing, emphasizing constraints, sampling, quantization, and their significance in systems requiring immediate signal response.

    Learning Practice

  • 13.2.1

    Real-Time Constraints

    This section discusses the essential constraints of real-time signal processing, focusing on latency, sampling rates, and throughput.

    Learning Practice

  • 13.2.2

    Sampling And Aliasing

    This section discusses the critical concepts of sampling and aliasing in real-time signal processing.

    Learning Practice

  • 13.2.3

    Quantization And Bit Depth

    This section discusses quantization and bit depth, emphasizing their impact on signal representation and quality in digital signal processing.

    Learning Practice

  • 13.3

    Matlab For Real-Time Signal Processing

    This section introduces MATLAB's toolboxes designed specifically for real-time signal processing, emphasizing their integration with Simulink for effective system modeling and execution.

    Learning Practice

  • 13.3.1

    Matlab Toolboxes For Signal Processing

    This section covers the essential MATLAB toolboxes that enhance signal processing capabilities in real-time applications.

    Learning Practice

  • 13.3.2

    Real-Time Simulation Environment

    This section outlines how MATLAB facilitates real-time simulation environments for signal processing, emphasizing tools like Simulink for execution and external mode simulation.

    Learning Practice

  • 13.4

    Signal Acquisition In Matlab

    This section discusses how to acquire and plot audio input in MATLAB, emphasizing real-time signal processing techniques.

    Learning Practice

  • 13.4.1

    Audio Input Using Matlab

    This section introduces audio input capabilities in MATLAB, showcasing how to use the audiorecorder function to capture audio signals.

    Learning Practice

  • 13.4.2

    Real-Time Plotting

    This section covers how to perform real-time plotting of audio signals in MATLAB to visualize the amplitude over time.

    Learning Practice

  • 13.4.3

    Using Dsp.audiorecorder

    This section covers how to use the dsp.AudioRecorder in MATLAB for real-time audio processing.

    Learning Practice

  • 13.5

    Real-Time Signal Filtering

    This section covers the design and application of FIR and IIR filters in real-time signal processing using MATLAB.

    Learning Practice

  • 13.5.1

    Fir And Iir Filters

    This section discusses FIR and IIR filters, their design using MATLAB, and their application for real-time signal processing.

    Learning Practice

  • 13.5.2

    Applying Filters In Real-Time

    This section focuses on real-time filtering of audio signals using MATLAB's DSP toolbox, allowing for immediate processing and output.

    Learning Practice

  • 13.6

    Real-Time Fourier Analysis

    This section covers the implementation of Fast Fourier Transform (FFT) and real-time spectrogram analysis using MATLAB.

    Learning Practice

  • 13.6.1

    Fast Fourier Transform (Fft)

    This section introduces the Fast Fourier Transform (FFT) as a tool for transforming signals from the time domain to the frequency domain using MATLAB.

    Learning Practice

  • 13.6.2

    Real-Time Spectrogram

    The Real-Time Spectrogram section discusses how to visualize audio signals in the frequency domain using spectrograms, which are crucial for analyzing the frequency content of signals over time.

    Learning Practice

  • 13.7

    Noise Removal And Enhancement

    This section discusses methods for identifying and removing noise from signals in real-time signal processing, focusing on Gaussian and impulse noise, and techniques like median and Wiener filtering.

    Learning Practice

  • 13.7.1

    Noise Identification

    This section discusses the common types of noise in signal processing, specifically Gaussian noise and impulse noise.

    Learning Practice

  • 13.7.2

    Real-Time Denoising Techniques

    This section focuses on effective techniques for denoising audio signals in real-time applications.

    Learning Practice

  • 13.8

    Real-Time Audio Effects Implementation

    This section introduces techniques for implementing audio effects in real-time using MATLAB, including echo and volume control.

    Learning Practice

  • 13.8.1

    Echo Effect

    This section discusses the implementation of the echo effect in real-time audio processing using MATLAB.

    Learning Practice

  • 13.8.2

    Volume Control

    This section explains the concept of volume control in real-time audio processing using MATLAB.

    Learning Practice

  • 13.9

    Real-Time Signal Visualization

    This section covers the techniques for visualizing signals in real-time using MATLAB, emphasizing both time-domain and frequency-domain representations.

    Learning Practice

  • 13.9.1

    Time-Domain Visualization

    This section introduces real-time time-domain visualization techniques for signal processing using MATLAB.

    Learning Practice

  • 13.9.2

    Frequency-Domain Visualization

    This section focuses on frequency-domain visualization techniques in real-time signal processing using MATLAB.

    Learning Practice

  • 13.10

    Simulink For Real-Time Systems

    This section highlights the use of Simulink for developing and simulating real-time systems, outlining key real-time blocks and execution modes.

    Learning Practice

  • 13.10.1

    Real-Time Blocks In Simulink

    This section covers essential real-time blocks in Simulink that are crucial for developing and simulating real-time signal processing applications.

    Learning Practice

  • 13.10.2

    External Mode Execution

    External Mode Execution allows for real-time execution of models on host or target systems while monitoring data.

    Learning Practice

  • 13.10.3

    Code Generation For Embedded Real-Time

    This section discusses code generation in Simulink and MATLAB for deploying real-time systems on embedded platforms like ARM Cortex, Arduino, and Raspberry Pi.

    Learning Practice

  • 13.11

    Case Study: Real-Time Voice Recorder And Playback

    This section focuses on creating a real-time voice recording and playback system in MATLAB, incorporating filtering and noise suppression.

    Learning Practice

  • 13.11.1

    Objective

    This section outlines the objective of building a real-time voice recording and playback system, emphasizing filtering and noise suppression.

    Learning Practice

  • 13.11.2

    Steps Involved

    This section outlines the steps required to create a real-time voice recording and playback system using MATLAB.

    Learning Practice

  • 13.12

    Challenges In Real-Time Processing

    This section outlines the primary challenges faced in real-time signal processing, including computational delays, memory management, and hardware integration.

    Learning Practice

  • 13.12.1

    Computational Delays

    Computational delays in real-time processing arise from heavy computations and system design limitations.

    Learning Practice

  • 13.12.2

    Memory Management

    Memory management in real-time systems is crucial to avoid buffer overflow and underflow, ensuring efficient signal processing.

    Learning Practice

  • 13.12.3

    Integration With Hardware

    This section discusses the essential aspects of integrating real-time signal processing systems with hardware, focusing on I/O latency, driver considerations, and the role of operating systems.

    Learning Practice

References

Chapter_13_Real.pdf

Class Notes

Memorization

What we have learnt

  • Signals can be classified i...
  • Apart from filtering, real-...
  • MATLAB provides specialized...

Final Test

Revision Tests