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An example is for high-resolution audio in which the frequency response (magnitude and phase) for steady state signals (sum of sinusoids) is the primary filter requirement, while an unconstrained impulse response may cause unexpected degradation due to time spreading of transient signals.
The impulse can be modeled as a Dirac delta function for continuous-time systems, or as the discrete unit sample function for discrete-time systems. The Dirac delta represents the limiting case of a pulse made very short in time while maintaining its area or integral (thus giving an infinitely high peak).
where the h[•] sequence is the impulse response, and K is its length. x [•] represents the input sequence being downsampled. In a general purpose processor, after computing y [ n ], the easiest way to compute y [ n +1] is to advance the starting index in the x [•] array by M , and recompute the dot product.
A sample is a value of the signal at a point in time and/or space; this definition differs from the term's usage in statistics, which refers to a set of such values. [ A ] A sampler is a subsystem or operation that extracts samples from a continuous signal .
The impulse response is a characterization of the filter's behavior. Digital filters are typically considered in two categories: infinite impulse response (IIR) and finite impulse response (FIR). In the case of linear time-invariant FIR filters, the impulse response is exactly equal to the sequence of filter coefficients, and thus:
Impulse response coefficients taken at intervals of form a subsequence, and there are such subsequences (called phases) multiplexed together. Each of L {\displaystyle L} phases of the impulse response is filtering the same sequential values of the x {\displaystyle x} data stream and producing one of L {\displaystyle L} sequential output values.
If a system initially rests at its equilibrium position, from where it is acted upon by a unit-impulse at the instance t=0, i.e., p(t) in the equation above is a Dirac delta function δ(t), () = | = =, then by solving the differential equation one can get a fundamental solution (known as a unit-impulse response function)
The impulse response can be computed to any desired degree of accuracy by choosing a suitable approximation for δ, and once it is known, it characterizes the system completely. See LTI system theory § Impulse response and convolution. The inverse Fourier transform of the tempered distribution f(ξ) = 1 is the delta function.