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digital-signal-processing

The convolution sum, derived from the sifting property

taught

Deriving y[n] = x[n]*h[n] from the sifting property plus linearity and time-invariance.

Taught in

Requires

Required by

Local knowledge map

Local knowledge map

Homogeneous and particular solutions of a difference… Reading a system's frequency response off its difference… Real-time FIR implementation -- the tapped delay line Recursive vs. non-recursive systems -- FIR vs. IIR The system function H(z), its poles, and its zeros Zero-input and zero-state response Convolution algebra -- commutativity, cascade, and parallel… Graphical and analytical convolution evaluation Linear constant-coefficient difference equations Numerical convolution: stream vs. block processing The convolution sum, derived from the sifting property Deterministic vs. random, periodic vs. aperiodic signals Energy signals and power signals Even and odd signals, and the even/odd decomposition Exponential and sinusoidal sequences Geometric series convergence NumPy array and indexing conventions for signals Discrete-time signal notation: $x[n]$ vs. $x(t)$ Linearity and time-invariance Continuous-time vs. discrete-time signals Sequence transformations: shifting and… System properties: memory, causality, and stability

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