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
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What we have learnt
- Signals can be classified into various types such as continuous-time and discrete-time.
- Apart from filtering, real-time systems require effective noise management and signal acquisition techniques.
- MATLAB provides specialized toolboxes that facilitate real-time simulation and deployment of signal processing applications.
Key Concepts
- -- RealTime Signal Processing
- Immediate processing of signals to provide instantaneous feedback or action in various systems.
- -- Nyquist Theorem
- A principle stating that a signal must be sampled at least twice the highest frequency to avoid aliasing.
- -- FIR Filters
- Finite impulse response filters used in signal processing to modify signal characteristics with a defined response.
- -- Quantization Noise
- The error introduced when continuous signals are converted to discrete form.
- -- Spectrogram
- A visual representation of the spectrum of frequencies in a signal as it varies with time.
Additional Learning Materials
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