LTI system causality and stability
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This document discusses causality and stability in digital signal processing. It covers impulse response, how response is determined through convolution sums, the concepts of causality and stability, and provides two example problems. Causality means the response of a system depends only on current and past inputs, not future inputs. Stability refers to a system where the response remains bounded for any bounded input signal. The document serves as lecture material from the Department of Electrical and Electronics Engineering at National Engineering College.
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This document compares infinite impulse response (IIR) systems and finite impulse response (FIR) systems. IIR systems are less powerful than FIR systems but require less processing power. FIR systems are more powerful but require more processing power. IIR systems are non-linear phase and cannot implement linear-phase filtering, while FIR systems can implement linear-phase filtering. FIR systems are also more stable than IIR systems since they do not utilize feedback. However, IIR systems generally require lower order filters than FIR systems to achieve the same performance.
kirchoff's law solved problems
https://www.youtube.com/watch?v=-fo2OYQD7q8
#Basiccircuitanalysis_kkk #U1 #EEE
Kirchhoff's circuit law |KCL, KVL|- Solved Problems (Lecture 10)
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#Basiccircuitanalysis_kkk #U1 #EEE
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- 3. RESPONSE THROUGH CONVOLUTION SUM
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