Next  |  Prev  |  Top  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

Index for this Document


3-dB bandwidth : 9.5 | 18.6
abstraction (pd) : 24.5.1
additive synthesis : 8.6.5
affine function : 11.5
allpass condition : 16
allpass filter : 15.2
biquad case : 15.2.1
examples : 16.1
general case : 16
allpass filter design : 15.2.2
Amperes : 18.2 | 18.3
amplifier modeling : 19.7
amplitude : 14.1.1
amplitude envelope : 8.6.5
amplitude response : 2.2 | 2.3.1 | 8.2
analog filters : 18 | 22.2
allpass : 18.8
capacitor impedance : 18.2
example : 18.1
example RC analysis : 18.4
example RLC analysis : 18.5
inductor impedance : 18.3
poles and zeros : 18.4.5
RL impulse response : 18.4.3
RLC impulse response : 18.5.4
second-order poles and zeros : 18.5.3
second-order transfer function : 18.5.2
transfer function : 18.4.2
analog prototype : 22.3.3
analytic continuation : 7.2 | 17.2 | 17.2 | 22.2.1
anticausal : 9.8
anticausal exponentials : 9.7
antiresonance frequency : 15.1.4 | 15.1.6
antiresonator : 15.1.4
antisymmetric impulse responses : 11.5
antisymmetric linear-phase filters : 11.5
banded Toeplitz filter matrix : 19.3
bandwidth of a pole : 9.5
bandwidth of a pole : 18.6
bilateral z transform : 7.1
bilateral Laplace transform : 17
bilinear transformation : 22.3.1
frequency warping : 22.3.2
prototype analog filters : 22
binomial coefficient : 20.10.1
biquad filter section : 7.8.3 | 15.1.6
blocking capacitor : 15.3
boost : 15.5
Butterworth filters : 22.2
Butterworth lowpass example : 10.2.4
Butterworth lowpass filter design example : 22.2.2
canonical with respect to delay : 6.11.6
capacitor : 18.2
capacitor driving point impedance : 18.4.1
capacitors as springs : 18.2.1
carrier frequency : 8.6.3.1
carrier term : 14.3.3
carrier wave : 8.6.5
causal : 5.3 | 6.3 | 16
causal filters : 6.3
causal signal : 7.1 | 24.1
center frequency of a resonator : 15.1.3
cepstrum
complex : 9.8
minimum phase : 9.9
poles and zeros : 9.8
real : 9.8
characteristic polynomial : 20.6
circulant matrix : 19.4
clipping : 5.1
clipping dB magnitude : 23.10
coefficients, difference equation : 6.1
comb filter : 4
commutativity of series filters : 7.7.2.1
companding : 5.7
complete response : 6.12.5 | 20.3
complex amplitude : 2.4.2
complex analysis : 5.1
complex and trig identities : 14.2
complex cepstrum : 9.8
complex exponential : 2.4.1 | 7.8.4
complex filter : 5.3 | 6.1
complex numbers summary : 14.2
complex one-pole sections : 10.2.2.1
complex resonator : 15.1.5 | 18.6
complex signal : 5.1
complex sinusoid : 2.4.1
complex sinusoidal oscillator : 15.1.5
condition number : 20.10
conformal map : 22.3.2
constant peak-gain resonator : 15.6.4
constant resonance-gain resonator : 15.6.2
continuous-time complex one-pole resonator : 18.6
controllability and observability : 20.7.3
controllable modes : 20.7.1
controller canonical form : 19.6.1 | 20.7.1
convex optimization : 22.1
convolution : 7.8.10.2 | 20.1
convolution filter representation : 6.9 | 6.10
convolution is commutative : 7.7.2.1
convolution theorem for z transforms : 7.3
convolution theorem for z transforms : 7.3.2
convolution theorem for z transforms : 7.3.2
Coulombs : 18.2
cps : 14.1.1
critically damped : 18.7
current : 18.2
cut filter : 15.5
cut-off frequency : 2.2
cycles per second : 14.1.1
cyclic convolution : 19.4
damping constant : 18.7
dB clipping : 23.10
dc blocker : 15.3
dc blocker frequency response : 15.3.1
dc blocking filter : 15.3
decay response : 6.12.4 | 6.12.4
decay time : 6.12.1
decay time-constant : 9.6
deconvolution : 7.8.10.3
degeneracy : 7.8.7
delay equalization : 8.6.4
delta function : 18.4.4
design of recursive digital filters : 22
determinant : 20.6
DFT matrix : 19.4
diagonalizing a state-space model : 20.9.1
difference equation : 6.1
differentiation theorem for Laplace transforms : 17.4.2
digital filter theory : 5
direct form filter implementation : 15.1.6
direct form filter implementations : 10.1
discrete Fourier transform (DFT) : 8.5.1
discrete time Fourier transform (DTFT) : 8.1
discrete-time sinusoid : 14.1.2
doublet : 17.5.1
driving point impedance
RLC network : 18.5.1
driving-point impedance : 18.2 | 18.3
DTFT : 8.1
Durbin recursion : 9.4.1 | 9.4.1
dynamic convolution : 5.9
dynamic range compression : 5.7
eigenvalues : 20.6 | 20.6
eigenvector : 20.9.1
electrical equivalent circuit : 17.5.1
equation error : 22.4.1
definition : 22.4.1
minimization : 22.4
equiripple : 8.6.4
error weighting function : 22.4.2
Euler's identity : 2.4
even impulse-response filter : 11.2
example elementary audio filters : 15
existence of the z transform : 7.2
explicit finite difference scheme : 6.1
exponential function summary : 14.2.1
exponential order : 17.1
exponentially swept sine analysis : 2.3.1
exponentially windowed : 17
externals (pd) : 24.5.1
factorial notation : 17.2
Farads : 18.2
Fast Fourier Transform (FFT) : 8.5.1
Faust programming language : 24
feedback coefficients : 6.1
feedback signal : 5.3
feedforward coefficients : 6.1
FFT convolution : 6.11.7 | 19.4
filter
allpass biquad : 15.2.1
allpass examples : 16.1
allpass sections : 15.2
amplitude response : 8.2
antiresonator : 15.1.4
antisymmetric impulse response : 11.5
biquad : 15.1.6
causal : 6.3
checking stability : 9.4.1
coefficients : 6.1
complete response : 6.12.5
complex : 6.1
complex one-pole resonator : 15.1.5
constant gain at resonance : 15.6.1
converting to minimum phase : 12.7
converting to parallel form : 7.8
dc blocker : 15.3
definition : 5.2 | 5.2
difference equation : 6.1
direct-form I : 6.2 | 6.5
direct-form II : 6.2 | 10.1.2
estimation from input/output data : 19.7
even impulse response : 11.2
examples : 5.3
feedback : 6.1
finite impulse response (FIR) : 6.11
first and second-order sections : 15.1
forming real second-order sections from two complex one-poles : 7.8.3
forward and backward : 11.6
frequency response : 8.1
frequency response in matlab : 8.5.1
general form of finite-order, causal, linear, time-invariant case : 6.4
graphical amplitude-response calculation from poles and zeros : 9.2
graphical phase response : 9.3
imaginary frequency response : 11.3
implementation structures : 6.2 | 10
complex resonators : 10.2.2.1
parallel second-order sections : 10.2.2
real second-order sections : 10.2.2.2
repeated pole : 10.2.2.3
second-order sections : 10.2
series second-order sections : 10.2.1
transposed direct-form II : 10.1.4
implementations
direct-form I : 10.1.1
direct-form II : 10.1.2
transposed direct forms : 10.1.3
internal overflow : 10.1.2
inverse : 19.5
linear : 5.4.2
linear phase : 11 | 11.4
linear time-varying : 21
linear, time invariant : 5
lossless : 16
LTI : 5.5
LTI matrix representation : 19.3
matrix representation : 19
minimum phase : 12
multi-input, multi-output (MIMO) allpass filters : 16.3
nonlinear example : 5.7
notch : 15.1.4
null : 15.1.4
odd impulse response : 11.3
one complex pole : 15.1.5
one pole : 15.1.2
one zero : 15.1.1
order : 6.4 | 6.4 | 9.1
paraconjugate : 16.2
parallel combination : 7.7
paraunitary, MIMO case : 16.3.1
paraunitary, SISO case : 16.2
partial fraction expansion : 7.8
peaking eq : 15.5
phase : 8.3
phase preserving : 11
phase response : 8.3
polar form of freq. response : 8.4
poles : 4.11
poles and zeros : 9
Q (quality factor) : 18.7
real : 6.1
real, digital : 5.2 | 5.2
recursive : 6.1
reflection coefficients : 9.4.1
resonance bandwidth of a pole : 18.6
resonator : 15.1.3
resonator bandwidth in terms of pole radius : 15.1.3.1
resonator center frequency : 15.1.3
series combination : 7.7
shelf : 15.4
shift-invariance : 5.5
signal flow graph (system diagram) : 6.2
simplest lowpass : 2
stability : 6.7 | 9.4
state space realization : 19.6
symmetric impulse response : 11.4
time-domain representations : 6
time-invariance : 5.5
transfer function : 7
transposition : 10.1.3
tunable resonator : 15.6.1
two pole : 15.1.3
two zero : 15.1.4
zero phase : 11.2
zeros : 4.11
filter design
analog prototype : 22.3.3
analog to digital conversion via bilinear transform : 22.3
Butterworth : 8.6.4 | 22.2
Chebyshev : 8.6.4
elliptic : 8.5.2 | 8.6.4
equation error method : 22.4
equation error minimization in the frequency domain : 22.4.4
frequency warping : 22.3.2
lowpass filter : 22.1
maximally flat amplitude response : 22.2
Padè-Prony method : 22.4.6
Prony's method : 22.4.5
Finite Impulse Response (FIR) digital filter : 6.11
finite support : 6.11.3
Finite-Impulse-Response (FIR) digital filter : 6.1
finite-order causal LTI digital filters : 6.4
FIR filter : 6.11 | 6.11
FIR filter design : 11.4.2
FIR part : 7.8.5
flip theorem for z transforms : 11.6
flow graph : 6.2
flow graph reversal : 10.1.3
folding a signal about index zero : 23.9
formant : 10.2.3
formant filtering : 10.2.3
forward-backward filtering : 11.6
frequencies : 14.1.1
frequency domain : 14.1.3
frequency response : 8.1
computation in matlab : 8.5.1
example in matlab : 8.5.2
imaginary : 11.3
frequency warping : 22.3.2 | 22.4.2
frequency-domain equation-error minimization : 22.4.4
frequency-response
measurement : 2.3
plotting in matlab : 23.4
gain at resonance : 15.6
generalized eigenvectors : 20.10
generalized function : 18.4.4
geometric sequence : 7.8.4
graphical computation of amplitude response from transfer-function poles and zeros : 9.2
graphical phase response calculation : 9.3
group delay : 8.6.3
computation : 8.6.6
example : 8.6.4
matlab function 1 : 23.8
matlab function 2 : 23.6
group delay equals modulation delay : 8.6.3.1
guard bits : 10.1.2.1
GUI generation : 24
Haar filter bank : 16.3.2
half-angle tangent identities : 14.2.3.1
half-open interval : 3.2
half-power bandwidth : 9.5 | 18.6
harmonic distortion : 5
Heaviside unit step function : 18.4.3
Henrys : 18.3
Hermitian : 11.2 | 11.3
Hertz (Hz) : 14.1.1
high shelf : 15.4
Hilbert transform relations : 9.10
Hooke's law for ideal springs : 18.2.1
Hurwitz polynomial : 18.8
impedance analysis : 18.4 | 18.5
implicit finite difference schemes : 6.1
impulse : 6.6
impulse invariant transformation : 18.6
impulse response : 6.6 | 6.11.1 | 12.2
example : 6.8
state-space model : 20.1
impulse signal : 4.6 | 6.6 | 6.11.1
impulse, continuous time : 18.4.4
inductor : 17.5.1 | 18.3
inductors as masses : 18.3.1
infinite-impulse-response (IIR) : 6.1
initial conditions : 20.2
initial state : 20.2
initial-condition response : 6.12.5
instantaneous frequency : 14.1.2
instantaneous phase : 14.1.2
intermodulation distortion : 5
interreciprocal : 10.1.3
inverse filter : 19.5
irreducible : 7.8.8
Jordan block : 20.10.1
Jordan canonical form : 20.10.1
Jordan form of a matrix : 20.10.1
ladder filter : 10.2.3
LADSPA plugins : 24.6
Laplace transform
analysis
linear systems : 17.5
mass-spring oscillator : 17.5.2
moving mass : 17.5.1
definition : 17
differentiation theorem : 17.4.2
existence : 17.1
linearity : 17.4.1
relation to z transform : 17.3
response to initial conditions : 17.5.1
theorems : 17.4
least-squares : 19.7
level-dependent gain : 5.7.1
Levinson recursion : 9.4.1
limiter : 5.7
linear algebra : 5.1
linear filter : 5.4.2
linear operator : 5.2
linear phase in audio applications : 12.6
linear prediction : 9.4.1
linear systems theory : 5
linear transformation : 5.2
linear, time-invariant filters : 5
linear-phase filter : 11 | 11.4
design : 11.4.2
examples : 11.4.1
linearity and time invariance : 5
log-swept sine-wave analysis : 2.3.1
logarithmic derivative : 8.6.6
long division : 7.8.5
lossless analog filters : 18.8.1
lossless filter : 15.2 | 16
examples : 16.1
lossless transfer function matrix : 16.3
losslessness implies allpass : 16
low shelf : 15.4
LTI filter matrix : 19.3
LTI filters : 5.5 | 5.10
LTI implications : 6.9
magnitude frequency response : 2.2 | 8.2
marginally stable : 9.4 | 9.4.2
Markov parameters : 20.1
Mason's gain formula : 10.1.3
Mason's gain theorem : 20.5
matched z transformation : 18.6
math summary : 14
matlab : 3
Matlab software : see softwaretextbf
matrices : 19.1 | 20
matrix : 5.2
matrix fraction descriptions : 5.2
matrix representations : 19
maximum-phase filters : 12.3
maximum-phase sequence : 12.3
median smoother : 5.3
memoryless nonlinearity : 5.3
message box (pd) : 24.5.1
MIMO digital filter : 5.2
minimum-delay sequence : 12.4
minimum-delay signals : 12.4
minimum-phase
filter : 12
polynomial : 12.2
sequence : 12.2
minimum-phase = fastest decay : 12.4
minimum-phase allpass decomposition : 12.5
minimum-phase computation from spectral magnitude data : 12.7
minimum-phase conversion of a spectrum : 23.11
minimum-phase filter design : 12.7
minimum-phase filters and signals : 12.7
minimum-phase sequence : 12.7
mixed-phase filter : 12.3
modal representation : 20.9 | 20.9 | 20.9.1
mode of vibration : 20.7.3
Moog VCF : 15.6.5
Moore-Penrose pseudoinverse : 19.7
moving average : 5.6
multi-input, multi-out (MIMO) digital filter : 5.2
multiplicity of a pole : 7.8.7.1
Muse Receptor : 24.7
negative-frequency component : 2.4.4
Newton's second law : 18.3.1
nonlinear distortion : 19.7
nonlinear filter : 5.7
analysis : 5.9
nonparametric signal processing : 12.7
nonrecursive digital filter : 6.1
normalized second-order resonator : 20.4.1
notch : 15.1.6
notch filter : 2.3.2
notch frequency : 15.1.4
null : 2.3.2
numerical issues : 10
observable modes : 20.7.3
observer canonical form : 20.7.1 | 20.7.2
Octave software : see softwaretextbf
odd impulse response : 11.3
one-off subpatch (pd) : 24.5.1
one-pole filter : 15.1.2
one-pole resonator, complex : 15.1.5
one-sided Laplace transform : 17
one-zero filter : 15.1.1
operator : 5.2
operator theory : 5.1
optimality in the Chebyshev sense : 8.6.4
order of a
filter : 6.4 | 9.1
pole : 17.2
polynomial : 9.1
rational function : 9.1
orthogonality principle : 19.7.1
output error minimization : 22.4.1
overdamped : 18.7
Padé-Prony method for filter design : 22.4.6
para-Hermitian conjugate : 8.6.6
paraconjugate transfer function : 16.2
parallel and series filter sections : 10.2.5
parallel combination : 7.7.2 | 18.5.1
parallel complex resonator : 10.2.2.1
parallel second-order filter sections : 4.12
parallel sos in matlab : 23.7
parametric equalizer : 15.5
paraunitary filter bank : 16.3.1.4
paraunitary MIMO filters : 16.3.1
partial fraction expansion : 4.12 | 7.8 | 10.2.2 | 15.1.5.1
alternate methods : 7.8.6
complex poles : 4.12.1
FIR part : 7.8.5
in matlab : 23.5
inversion : 7.8.4
repeated pole : 7.8.7 | 7.8.7.1
second order sections : 7.8.3
software : 7.8.10
summary : 7.8.9
passband : 2.2 | 8.5.2 | 11.2
pd
abstraction : 24.5.1
externals : 24.5.1
plugins : 24.5
subpatch : 24.5.1
peak filter : 15.5
peak gain : 15.6 | 15.6.3
peak gain versus resonance gain : 15.6.3
peaking eq filters : 15.5
perfect reconstruction filter bank : 16.3.1.4
periodic signal : 14.1.1
phase : 14.1.2
phase delay : 8.6.1
phase dispersion : 8.6.3 | 11.7
phase offset : 14.1.2
phase quadrature : 20.11.2
phase response : 2.3.1 | 8.3
phase unwrapping : 8.6.2
phasor : 2.4.3 | 14.3.3
phasor analysis : 2.4.3 | 14.3.2 | 14.3.3
phasor representation : 2.4.3
piecewise constant-phase filters : 11.2.2
plot
frequency data : 23.2
saving to disk : 23.3
plugin wrapper (pd) : 24.5.2
plugins : 24
LADSPA : 24.6
pd : 24.5
VST : 24.7
polar form of freq. response : 8.4
pole : 17.2
bandwidth : 9.5
frequency : 15.1.3
order : 17.2
time-constant : 9.6
pole-zero analysis : 4.11
poles : 4.11 | 7.6 | 7.8 | 9
poles and zeros : 9
poles of a state-space model : 20.6
poles outside unit circle : 9.7
polynomial
division in matlab : 7.8.10.3
long division : 7.8.10.3
multiplication : 7.8.10.2
multiplication in matlab : 7.8.10.2
order : 9.1
polynomial amplitude envelopes : 7.8.7.3
positive-frequency sinusoid : 2.4.4
predelay : 7.8.5
problems : see exercisestextbf
projection error : 19.7.1
Prony's method : 22.4.5
pseudoinverse : 19.7
Q (quality factor) : 18.7
relation to decay time : 18.7.1
radians per second : 14.1.1
ratio test : 17.2
rational function : 9.1
RC time constant : 18.4.2
real filter : 2.3.2 | 5.2 | 6.1 | 7.8.3
real signal : 5.1
real, even-impulse-response filter : 11.2
real-frequency-response filter : 11.2
Receptor : 24.7
recursive filter : 5.3 | 6.1
reflecting zeros inside unit circle : 9.9
reflection coefficients : 9.4.1
region of convergence : 9.7
repeated pole : 20.10
impulse response : 7.8.7.3
residue : 7.8
resonance : 15.1.3
resonant frequency : 18.7
resonator : 15.1.3
resonator bandwidth : 18.6
response to initial conditions : 6.12.4
right-half plane : 17
ring time : 6.12.1
ripple : 8.5.2
rms level : 5.7.1
roll-off : 8.5.2
running weighted sum : 5.6
samples : 14.1.1
sampling interval : 14.1.1
scalars : 5.1
scaling property of linear systems : 5.4.2
Schur recursion : 9.4.1
Schur-Cohn stability test : 9.4.1 | 9.4.1
seconds : 14.1.1
series and parallel filter sections : 10.2.5
series and parallel transfer functions : 7.7
series connection : 7.7.1
series second-order sections : 10.2.1
set notation : 5.1
shelf filters : 15.4
shift operator : 5.5
shift theorem for z transforms : 7.3
shift theorem for z transforms : 7.3.1
shift-invariant filter : 5.5
sideband images : 5
sifting property : 18.4.4
signal
complex, discrete-time : 5.1 | 5.1
definition : 5.1
flow graph : 6.2
operator : 5.4.2
plotting in matlab : 23.1 | 23.13
real, discrete-time : 5.1 | 5.1
representation : 14.1
signal flow graph : 4.2
signal space : 5.1
similarity transformation : 20.8 | 20.9.1
simple lowpass filter
analysis in matlab : 3 | 3.2 | 3.3 | 3.4
matlab implementation : 3.1
simulation diagram : 2.2.1 | 6.2
sinc function : 11.2.2
sine-wave analysis : 2.3.1 | 2.3.2 | 2.4.5
single-input, single-output (SISO) digital filters : 5.2
singular matrix : 20.10
sinusoid : 14.1.2
SISO digital filter : 5.2
sliding linear combination : 5.6
software : 23
Faust programming : 24
Matlab
frequency-response plot : 23.4 | 23.13
signal plots : 23.1
Matlab or Octave
clipping dB magnitude : 23.10
folding a signal about index zero : 23.9
frequency plots : 23.2
frequency-response computation : 8.5.1
group delay computation : 23.8
minimum phase conversion : 23.11
parallel second-order sections : 23.7
partial fraction expansion : 23.5 | 23.6
saving plots : 23.3
Octave
signal plots : 23.1
spectrum : 14.1.3
speech modeling : 9.4.1
speech synthesis : 10.2.3
split-radix FFT : 3.4
spring
compliance : 18.2.1
constant : 18.2.1
stiffness : 18.2.1
stability of a digital filter : 6.7 | 7.8.8 | 9.4
state space filter : 20
analysis : 20
analysis example
the digital waveguide oscillator : 20.11
complete response : 20.3
computation : 20.7.6
diagonalization : 20.9.1
example : 19.6.1
from difference equations : 20.7
impulse response : 20.1
matlab : 20.7.8
modal representation : 20.9
poles : 20.6
realization : 19.6 | 20
response from initial conditions : 20.2
similarity transformation : 20.8
transfer function : 20.4
transfer function example : 20.4.1
transposition : 20.5
state space realization : 7.8.6
steady state
analysis : 18.2
response : 6.12
signal : 6.12.3
Steinberg Media Technologies : 24.7
step-down procedure : 9.4.1
stopband : 2.2 | 8.5.2
strict right-half plane : 17
strictly proper transfer function : 7.8.3
subpatch (pd) : 24.5.1
sum of sinusoids : 14.3
superposition property : 5.4.2
superposition property of linear systems : 5.4.2 | 6.10
swanalmainplot : 23.13
swanalplot : 23.12
symmetric impulse response : 11.1 | 11.1
symmetric linear-phase FIR filter : 11.4
synthesis filter bank : 16.3.1.4
system diagram : 4.2 | 6.2
system function : 7
system identification : 19.7 | 19.7
tapped delay line : 6.11
Taylor series expansion : 2.4
Tellegen's theorem : 10.1.3
time constant : 9.6
time constant of a pole : 9.6
time domain : 14.1.3
time reversal inverts the locations of all zeros : 12.3
time-delay spectrometry : 2.3.1
time-invariant filter : 5.5 | 5.5
time-varying
filter coefficients : 15.6
filter example : 5.8
two-pole digital filters : 15.6
Toeplitz linear operator : 19.3
Toeplitz matrix : 19.3
transfer characteristics : 7
transfer function : 6.11.5 | 7
factored : 7.6
matrix : 20.4
of a state space filter : 20.4
to second-order-section matlab function tf2sos : 10.2.1
transient : 6.12.3 | 6.12.3
transient response : 6.12
transition band : 8.5.2
transition frequency : 15.4
transpose of a filter : 10.1.3 | 20.5
transposed direct form I (TDF-I) : 10.1.3
transposed direct form II (TDF-II) : 10.1.3
transposing the signal flow graph : 20.5
transversal filter : 6.11
tremolo : 5.8
trig identities : 14.2
trigonometric identity summary : 14.2.2
tunable two-pole digital filters : 15.6
two's complement wrap-around : 10.1.1.1
two-pole filter : 15.1.3
two-pole partial fraction expansion : 15.1.5.1
two-pole time-varying filter : 15.6
two-sided Laplace transform : 17
two-zero filter : 15.1.4
undamped : 18.7
underdamped : 18.7
unilateral z transform : 7.1
unilateral Laplace transform : 17
unit step function : 6.8 | 15.1.5
unstable poles : 9.7
unwrapping phase : 8.6.2
variable resonator : 15.6.1
variable two-pole digital filters : 15.6
VCF : 15.6
vector coordinate : 5.1
vector space : 5.1
vectorized algorithms : 3.1
virtual analog synthesis : 15.6.5
vocoder : 8.6.5
voltage divider rule : 18.4.2
voltage-controlled filters : 15.6
Volterra kernels : 5.9
vowel simulation : 10.2.3
VST plugins : 24.7
wave digital filters : 22.3.4
weighting function : 22.4.2
window method for FIR filter design : 22.1
z transform : 7.1
existence : 7.2
theorems
convolution : 7.3.2
shift : 7.3.1
zero at infinity : 18.4.5
zero initial state : 20.1
zero padding : 3.4 | 19.3 | 19.4
zero-input response : 19.6.1
zero-phase filter : 11.2
examples : 11.2.1 | 11.2.2
zero-state response : 6.12.5
zeros of a filter : 4.11


Next  |  Prev  |  Top  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

[How to cite this work]  [Order a printed hardcopy]  [Comment on this page via email]

``Introduction to Digital Filters with Audio Applications'', by Julius O. Smith III, (September 2007 Edition).
Copyright © 2014-03-23 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
CCRMA