Introduction to Digital Filters

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23 Terms

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A discrete time signal is the ___ of scaled and _ --- impulses

sum of scaled and delayed impulses

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Discrete time systems

A systems that maps input sequence to an output sequence

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superposition

weighted sum of inputs = weighted sum of outputs

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A linear systems obeys the principle of

superposition i.e weighted sum of inputs = weighted sum of outputs

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The principle of superposition consists of

Additivity and Homogeneity (scaling)

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Time invariant systems

a time shift in the input results a in a corresponding time shift in the output

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Discrete time signal representation is given as

x[k]δ[n-k]

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LTI Systems response is aka the

Convolution sum

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impusle response

systems output given to an impulse input

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in the time domain, LTI systems are characterised by their

Impulse Response

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Convolution properties

Commutative

Associative

Distributive

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Constant Coefficient Difference Equations

y[n] = ∑bx[n-k] - ∑ay[n-k]

weighted sum of current input and previous input and output

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The order of the filter and the length of the filter is given as

N and N+1

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IIR

Infinite Impulse Response

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FIR

Finite Impulse Response

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IIR filter is one which has dependence on previous output

Yes it has, The FIR doesn’t depend on previous outputs

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IIR filter has a finite response to a single impulse

No it has unlimited response but FIR has finite response

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Casual system depends

only on the current and present inputs but not future inputs

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Response of the LTI system to an sinusoidal input is

the scaled magnitude and phase version of the sinusoid

y[n] = H(Ω)exp(jΩn)

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exp(jΩn) is the ___ AND H(Ω) is the _--

Eigenfunction and Eigen value

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to ensure stablity in the z domain

the poles must be within the unit circle

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if p1 > 1 in a first order c transform what occurs

exponential growth in Output.

y[n] = p^n for n >= 0

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