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The basic recursive equation for the scaling function, defined in [link] as

φ ( t ) = n h ( n ) 2 φ ( 2 t - n ) ,

is homogeneous, so its solution is unique only within a normalization factor. In most cases, both the scaling function and wavelet arenormalized to unit energy or unit norm. In the properties discussed here, we normalize the energy as E = | φ ( t ) | 2 d t = 1 . Other normalizations can easily be used if desired.

General properties not requiring orthogonality

There are several properties that are simply a result of the multiresolution equation [link] and, therefore, hold for orthogonal and biorthogonal systems.

Property 1 The normalization of φ ( t ) is arbitrary and is given in [link] as E . Here we usually set E = 1 so that the basis functions are orthonormal and coefficients can easily be calculated with inner products.

| φ ( t ) | 2 d t = E = 1

Property 2 Not only can the scaling function be written as a weighted sum of functions in the next higher scale space as stated in the basic recursion equation [link] , but it can also be expressed in higher resolution spaces:

φ ( t ) = n h ( j ) ( n ) 2 j / 2 φ ( 2 j t - n )

where h ( 1 ) ( n ) = h ( n ) and for j 1

h ( j + 1 ) ( n ) = k h ( j ) ( k ) h ( j ) ( n - 2 k ) .

Property 3 A formula for the sum of dyadic samples of φ ( t )

k φ ( k 2 J ) = 2 J

Property 4 A “partition of unity" follows from [link] for J = 0

m φ ( m ) = 1

Property 5 A generalized partition of unity exists if φ ( t ) is continuous

m φ ( t - m ) = 1

Property 6 A frequency domain statement of the basic recursion equation [link]

Φ ( ω ) = 1 2 H ( ω / 2 ) Φ ( ω / 2 )

Property 7 Successive approximations in the frequency domain is often easier to analyze than the time domain version in [link] . The convergence properties of this infinite product are very important.

Φ ( ω ) = k = 1 1 2 H ( ω 2 k ) Φ ( 0 )

This formula is derived in [link] .

Properties that depend on orthogonality

The following properties depend on the orthogonality of the scaling and wavelet functions.

Property 8 The square of the integral of φ ( t ) is equal to the integral of the square of φ ( t ) , or A 0 2 = E .

φ ( t ) d t 2 = φ ( t ) 2 d t

Property 9 The integral of the wavelet is necessarily zero

ψ ( t ) d t = 0

The norm of the wavelet is usually normalized to one such that | ψ ( t ) | 2 d t = 1 .

Property 10 Not only are integer translates of the wavelet orthogonal; different scales are also orthogonal.

2 j / 2 ψ ( 2 j t - k ) 2 i / 2 ψ ( 2 i t - ) d t = δ ( k - ) δ ( j - i )

where the norm of ψ ( t ) is one.

Property 11 The scaling function and wavelet are orthogonal over both scale and translation.

2 j / 2 ψ ( 2 j t - k ) 2 i / 2 φ ( 2 i t - ) d t = 0

for all integer i , j , k , where j i .

Property 12 A frequency domain statement of the orthogonality requirements in [link] . It also is a statement of equivalent energy measures in the time and frequency domains as in Parseval's theorem, which is true with anorthogonal basis set.

k | Φ ( ω + 2 π k ) | 2 = | Φ ( ω ) | 2 d ω = | φ ( t ) | 2 d t = 1

Property 13 The scaling coefficients can be calculated from the orthogonal or tight frame scaling functions by

h ( n ) = 2 φ ( t ) φ ( 2 t - n ) d t .

Property 14 The wavelet coefficients can be calculated from the orthogonal or tight frame scaling functions by

h 1 ( n ) = 2 ψ ( t ) φ ( 2 t - n ) d t .

Derivations of some of these properties can be found in Appendix B . Properties in equations [link] , [link] , [link] , [link] , [link] , [link] , and [link] are independent of any normalization of φ ( t ) . Normalization affects the others. Those in equations [link] , [link] , [link] , [link] , [link] , [link] , and [link] do not require orthogonality of integer translates of φ ( t ) . Those in [link] , [link] , [link] , [link] , [link] , [link] , [link] require orthogonality. No properties require compact support. Many of the derivations interchangeorder of summations or of summation and integration. Conditions for those interchanges must be met.

Questions & Answers

A golfer on a fairway is 70 m away from the green, which sits below the level of the fairway by 20 m. If the golfer hits the ball at an angle of 40° with an initial speed of 20 m/s, how close to the green does she come?
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Nevermind i just realied that the graph is the phons output for a person with normal hearing and not just the phons output of the sound waves power, I should read the entire thing next time
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Source:  OpenStax, Wavelets and wavelet transforms. OpenStax CNX. Aug 06, 2015 Download for free at https://legacy.cnx.org/content/col11454/1.6
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