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Search Mathematics of the DFT

  

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Index


20 dB boost : 15.2.1
3 dB boost : 15.2.1
coherenceml : 9.6.1
A-weighted dB scale : 15.2.2.4
absolutely integrable : 11.2.1
ADSR envelope : 8.2.4.4
alias operator : 8.2.15
aliased sinc function : 7.7 | 8.4.13
aliasing : 8.2.15 | 13.2
aliasing operator : 8.2.15
aliasing theorem : 8.4.11
continuous time : 13.2.1
AM index : 5.3.5
amplitude of a sinusoid : 5.1
amplitude response : 9.3.2
analytic signal : 5.3.7
anti-aliasing lowpass filter : 8.2.15
anti-Hermitian : 8.4.2
antilinear : 6.9.1
antilogarithm, antilog : 15.1
antisymmetric functions : 8.3
Argand diagram : 3.6
attack level : 8.2.4.4
autocorrelation : 9.4.3
average power : 6.8 | 16.3
Banach space : 6.8.3
bandlimited : 4.8
bandlimited downsampling : 8.2.14
bandlimited interpolation : 8.4.13
of spectra : 8.2.11
time or frequency domain : 8.2.11
bandlimited signals cannot be time limited : 12.3
base (of a logarithm) : 15.1
beats : 5.3.5
bel : 15.2
Bessel function : 5.3.6.1
Bessel generating function : 5.3.6.1
bin number (DFT) : 7.8
bin numbers : 7.8
bits (binary digits) : 16.1.2
Blackman window : 9.1.4
Bluestein FFT : 10.4
cardinal sine : 13.1.2
carrier wave : 5.3.5 | 5.3.11.1
Cartesian coordinates : 3.6
Cauchy-Schwarz inequality : 6.9.3
causal : 5.3.12 | 8.2.4.3
causal signal : 8.2.8
causal signals : 8.2.8
causal signals, periodic : 8.2.8
causal zero padding : 8.2.9
causalperiodicsignals : 8.2.8
characteristic of a logarithm : 15.1
chirp signals : 10.4
chirp z transform algorithm : 10.4
circular convolution : 8.2.4
circular cross-correlation : 9.4.1
click removal : 9.4.2
CODEC : 16.2.3
coefficient of projection : 7.6
coherence function : 9.6 | 9.6
column vector : 17.1
comb filter : 5.1.5 | 5.1.5
common logarithm : 15.1
commutativity of convolution : 8.2.4.1
companding : 15.2.3
completing the square : 3.2
complex amplitude : 5.3.11.1
complex conjugate : 3.7
complex matrix : 17
complex matrix transpose : 17
complex multiplication : 3.5
complex numbers : 3 | 3.3 | 3.5 | 3.7
complex numbers in matlab : 18.1
complex plane : 3.6
complex roots of a polynomial : 3.3
complex vector space : 6.10.4
complexity of FFT : 10.1.2.1
conjugation and reversal symmetries (DFT) : 8.4.2
constant modulus : 5.3
continuous-time aliasing : 13.2.1
convolution : 8.2.4 | 8.2.4
ADSR example : 8.2.4.4
filter interpretation : 8.2.4.2
filter representation : 9.3
frequency domain : 8.4.6
graphical : 8.2.4.6
matched filter example : 8.2.4.5
smoother example : 8.2.4.3
convolution as a filter : 8.2.4.2
convolution commutativity : 8.2.4.1
convolution theorem : 8.4.5
convolution theorem dual : 8.4.6
correlation : 8.2.5
correlation analysis : 9.4
correlation operator : 8.2.5
correlation theorem : 8.4.7
cosine, two vectors : 6.9.6
cps : 5.1
critical bandwidth of hearing : 5.3.5
cross-correlation : 9.4.1
cross-correlation, circular : 9.4.1
cross-correlation, unbiased : 9.4.2
cross-covariance : 9.4.3
cross-spectral density : 9.4.1
cross-talk : 7.7
cubic spline : 14.5
cycles per second : 5.1
cyclic convolution : 8.2.4
dB for display : 15.2.2.5
dB per decade : 15.2.1
dB per octave : 15.2.1
dB properties : 15.2.1
dB scale : 15.2
dB SPL : 15.2.2.3
dBA : 15.2.2.4
dBm scale : 15.2.2.1
dBV scale : 15.2.2.2
DCT : 10.6.1
de Moivre's theorem : 3.10
de Moivre's theorem, proof : 4.15
decibel : 15.2
decimal numbers : 16.1.2
decimation : 8.2.14
decimation in frequency : 10.1.1
decimation in time : 10.1.1 | 10.1.1
decimation theorem : 8.4.11
delta function : 11.2.2
DFT : 7
applications : 9
as a digital filter : 7.7
bin amplitude response : 18.4.2
definition : 2.1
math outline : 2.4
normalized : 7.10
DFT mathematics overview : 2.3
DFT matrix : 7.12 | 7.12
DFT matrix in matlab : 18.4.3
DFT sinusoids : 7.2.2 | 18.4.1
differentiability of audio signals : 14.6
differentiation theorem : 12.1
digit : 16.1.2
digital filter : 9.3
Discrete Cosine Transform (DCT) : 10.6.1
Discrete Fourier Transform (DFT) : 2.1 | 7 | 8.1
Discrete Time Fourier Transform (DTFT) : 11.1
downsampling operator : 8.2.14
downsampling theorem : 8.4.11
DTFT : 11.1
duality (Fourier) : 8.4.6
dynamic range : 15.2.3
dynamic range of magnetic tape : 15.2.3
energy : 15.2
energy of a signal : 6.8
energy theorem : 8.4.9 | 8.4.9
entire function : 5.3.6.1
essential singularity : 14.5
Euclidean norm : 6.8
Euler's Identity : 3.9 | 3.9 | 4 | 15.1.2
even and odd functions : 8.3
even functions : 8.3
exp(j theta) : 4.12
expected value : 16.3
exponent : 15.1
exponentials : 5.2
exponents
properties of : 4.3
rational : 4.6
factored form of a polynomial : 3.1
factoring a polynomial : 3.1
fast convolution : 8.4.5
Fast Fourier Transform (FFT) : 10
feedback FM : 5.3.6
FFT : 10
audio signal processing : 10.5
Bluestein FFT : 10.4
complexity : 10.1.2.1
decimation in time : 10.1.1
mixed-radix Cooley-Tukey : 10.1
number theory transform : 10.6.2
Rader FFT : 10.3
radix 2 : 10.1.2
software : 10.7
FFT notation : 8.1.1
FFT window : 7.7 | 9.1.4
filter : 8.2.4.2
flip operator : 8.2.2 | 8.2.2
FM index : 5.3.6.2
FM modulation frequency : 5.3.6.1
FM synthesis spectrum : 5.3.6.2
folding frequency : 8.4.13
formants : 9.2.1
Fourier duality : 8.4.6
Fourier series : 7.9
Fourier series and the DFT : 11.3
Fourier series coefficient : 11.3
Fourier symmetries : 8.4.3
Fourier theorems : 8 | 8.4
Fourier theorems (DFT) : 8 | 8.4
aliasing theorem : 8.4.11
convolution theorem : 8.4.5
convolution theorem dual : 8.4.6
correlation theorem : 8.4.7
downsampling theorem : 8.4.11
energy theorem (Rayleigh) : 8.4.9
Parseval's theorem : 8.4.8
periodic interpolation (in time) : 8.4.13
power theorem : 8.4.8
shift theorem : 8.4.4
stretch (repeat) theorem : 8.4.10
zero-padding (spectral interpolation) theorem : 8.4.12
Fourier transform : 11.2
Fourier transform cases : 11
Fourier transform existence : 11.2.1
Fourier Transform theorems : 12
continuous-time aliasing : 13.2.1
differentiation : 12.1
scaling or similarity : 12.2
uncertainty principle : 12.3
frame : 8.2.10
frequency bin : 7.8
frequency domain : 5.1.6
frequency modulation : 5.3.6 | 5.3.6
frequency resolution : 5.3.5
frequency response : 9.3.1
frequency-domain aliasing : 8.2.15 | 8.2.15
FS (Fourier Series) : 11.3
FT (Fourier Transform) : 11.2
fundamental theorem of algebra : 3.4
Gaussian function : 12.3.1
generalized function : 11.2.2
generating function : 5.3.6.1
geometric sequence : 7.1
geometric sequence frequencies : 13.4
geometric series : 7.1 | 7.1
geometric signal theory : 6
Gibb's phenomenon : 7.7
Good-Thomas FFT algorithm : 10.2
Gram-Schmidt orthogonalization : 6.10.6
graphical convolution : 8.2.4.6
half-open interval : 8.1
Hann window : 9.1.5
Hanning window : 9.1.5
Heisenberg uncertainty principle : 12.3.1
Hermitian spectra : 8.4.3
Hermitian symmetry : 8.4.2
Hermitian transpose : 6.9 | 7.12 | 17
Hertz : 5.1
hexadecimal : 16.1.2
Hilbert transform : 5.3.7
Hz : 5.1
ideal lowpass filter : 8.4.13.1
idempotent : 18.3.5
identity matrix : 17.1
IDFT : 2.2 | 8.1
imaginary exponents : 4.9
imaginary part : 3.5
impulse response : 8.2.4.2 | 9.3
impulse signal : 8.2.4.2 | 9.3
impulse train : 11.3.1
impulse, continuous time : 11.2.2
impulse-train signal : 8.2.4.2
indicator function : 8.4.4.2
inner product : 6.9
inner product in matlab : 18.3.3
integrable function : 11.2.1
intensity : 15.2
intensity level : 15.2.2.3
interpolation kernel : 13.1.2
interpolation operator : 8.2.12 | 8.2.12
inverse DFT : 2.2 | 8.1
inverse DFT matrix : 7.12
irrational number : 4.7
ITU-R 468 noise weighting : 15.2.2.4
just-noticeable difference (JND) : 15.2
lag : 8.2.5
lagged product : 8.2.5
linear algebra : 6.10.6
linear combination : 5.3.11.2 | 6.6
linear number systems for digital audio : 16.1
linear phase : 8.4.4.2
linear phase FFT windows : 8.4.4.4
linear phase signals : 8.4.4.2
linear phase term : 8.4.4 | 8.4.4.1 | 8.4.4.1
linear transformation : 17.1
linear vector space : 6.7
linear, time-invariant filters and convolution : 9.3
linearity of the DFT : 8.4.1
linearly dependent : 6.10.4
linearly independent : 6.10.2
logarithm : 15.1
logarithmic number systems for audio : 16.2
logarithms
changing the base : 15.1.1
of imaginary numbers : 15.1.2
loudness : 15.2.2.3
lowpass filter (ideal) : 8.4.13.1
Lp norms : 6.8.1
machine epsilon : 18.3.5.2
Maclaurin series : 14.3
magnitude of a sinusoid : 5.1
magnitude spectrum : 5.1.6
main lobe : 7.7
mantissa : 15.1
matched filter : 8.2.4.5 | 8.2.4.5
matlab listings
coherence function : 9.6.1
complex numbers : 18.1
DFT bin response : 18.4.2
DFT matrix : 18.4.3
factoring polynomials : 18.2
inner product : 18.3.3
orthogonalization : 18.3.6
signal energy, power : 18.3.2.1
signal metrics : 18.3.2
spectrogram : 18.5
subspace projection : 18.3.5
vector cosine : 18.3.4
Matlab/Octave examples : 18
matrix : 17
matrix multiplication : 17.1
matrix transpose : 17
maximally flat : 14.2
mean of a random variable : 16.3
mean of a signal : 6.8 | 16.3
mean square : 6.8 | 16.3
mean value : 16.3
mixed radix : 10.1
mixed-radix FFT : 10.1
modulation index : 5.3.5
modulo : 8.1.2
modulo indexing : 8.1.2
moments of a function : 16.3
monic polynomial : 3.1
Mth roots of unity : 4.13
mu-law coding : 16.2.3
multiplication in the time domain is convolution in the frequency domain : 8.4.6
multiplication of large numbers : 15.1
multiplying two numbers convolves their digits : 8.2.4.8
natural logarithm : 15.1
NDFT : 7.10
non-removable singularity : 14.5
nonlinear system of equations : 3.1
norm of DFT Sinusoids : 7.4
norm properties : 6.8.2
normalized inverse DFT matrix : 7.12
normalized DFT : 7.10 | 8.4.9
normalized DFT matrix : 7.12
normalized DFT sinusoids : 7.5 | 7.5 | 7.10 | 8.4.8.1
normalized frequency : 8.1
normalized radian frequency : 11.1
normed : 6.8.3
normed linear vector space : 6.8.3
Nth roots of unity : 7.2.1
number systems for digital audio : 16
byte swapping : 16.1.5
fixed point
one's complement : 16.1.2.1
two's complement : 16.1.2.2
floating point : 16.2.1
fractional fixed point : 16.1.3
how many bits are enough : 16.1.4
logarithmic : 16.2
logarithmic fixed point : 16.2.2
mu law : 16.2.3
PCM : 16.1.1
number theoretic transform : 10.6.2
Nyquist limit : 8.4.13 | 13
Nyquist rate : 8.4.13 | 13
Nyquist sampling theorem : 13
octal : 16.1.2
Octave : 18
Octave Symbolic Manipulation Toolbox : 4.7 | 4.11
odd and even functions :