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・ Orthogonal Defect Classification
・ Orthogonal diagonalization
・ Orthogonal frequency-division multiple access
・ Orthogonal frequency-division multiplexing
・ Orthogonal functions
・ Orthogonal group
・ Orthogonal instruction set
・ Orthogonal matrix
・ Orthogonal polarization spectral imaging
・ Orthogonal polynomials
・ Orthogonal polynomials on the unit circle
・ Orthogonal Procrustes problem
・ Orthogonal symmetric Lie algebra
・ Orthogonal trajectory
・ Orthogonal transformation
Orthogonal wavelet
・ Orthogonality
・ Orthogonality (programming)
・ Orthogonality (term rewriting)
・ Orthogonality principle
・ Orthogonalization
・ Orthogonia
・ Orthogonia grisea
・ Orthogonia plana
・ Orthogonia plumbinotata
・ Orthogoniinae
・ Orthogonioptelum
・ Orthogoniosaurus
・ Orthogonius
・ Orthogonius acrogonus


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Orthogonal wavelet : ウィキペディア英語版
Orthogonal wavelet
An orthogonal wavelet is a wavelet whose associated wavelet transform is orthogonal.
That is, the inverse wavelet transform is the adjoint of the wavelet transform.
If this condition is weakened one may end up with biorthogonal wavelets.
== Basics ==
The scaling function is a refinable function.
That is, it is a fractal functional equation, called the refinement equation (twin-scale relation or dilation equation):
:\phi(x)=\sum_^ a_k\phi(2x-k),
where the sequence (a_0,\dots, a_) of real numbers is called a scaling sequence or scaling mask.
The wavelet proper is obtained by a similar linear combination,
:\psi(x)=\sum_^ b_k\phi(2x-k),
where the sequence (b_0,\dots, b_) of real numbers is called a wavelet sequence or wavelet mask.
A necessary condition for the ''orthogonality'' of the wavelets is that the scaling sequence is orthogonal to any shifts of it by an even number of coefficients:
:\sum_ a_n a_=2\delta_
In this case there is the same number ''M=N'' of coefficients in the scaling as in the wavelet sequence, the wavelet sequence can be determined as b_n=(-1)^n a_. In some cases the opposite sign is chosen.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
ウィキペディアで「Orthogonal wavelet」の詳細全文を読む



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