1. Discrete-Time Signals and Systems: Convolution and Correlation
Discrete-time signals are sequences representing sampled quantities from continuous data, pivotal in Digital Signal Processing (DSP). Key concepts such as convolution and correlation allow analysis and manipulation, particularly in filtering and pattern recognition. The chapter delves into various properties, applications, and examples, establishing convolution and correlation as core operations in DSP.
Sections
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What we have learnt
- Discrete-time signals are vital for Digital Signal Processing.
- Convolution describes the interaction between input signals and systems based on impulse responses.
- Correlation measures the similarity between two discrete-time signals across various time lags.
Key Concepts
- -- DiscreteTime Signal
- A signal defined only at discrete intervals, typically obtained through sampling a continuous signal.
- -- Convolution
- A mathematical operation that describes the output of a linear time-invariant (LTI) system based on its input and impulse response.
- -- Correlation
- A method to measure the similarity between two signals as a function of the time-lag applied to one of them.
- -- Impulse Response
- The output of a system when an impulse signal is applied, reflecting how a system responds to inputs.
Additional Learning Materials
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