njit-etd2003-081 - New Jersey Institute of Technology
njit-etd2003-081 - New Jersey Institute of Technology njit-etd2003-081 - New Jersey Institute of Technology
67 3.7.1 Continuous Wavelet Transform The continuous wavelet transform maps a function f (t) onto time-scale space as This operation can be expressed in a simpler inner product notation as ψab (t) represents a family of functions obtained from a single wavelet function ψ (t) and the dilation and translation parameters a and b as where a and b are continuous. The wavelet function ψ(t) is a band-pass function. It is desired that this function have a good time and frequency localization so that f (t) is decomposed into elementary building blocks which are jointly well localized in time and frequency. The wavelet function has to satisfy the "admissibility" condition that makes it an isometry (up to a constant) of I! (R) onto 1,2 (R x R) . This requirement limits the wavelet functions which must satisfy [45][46] where ψ(Ω) is the Fourier transform of the wavelet function ψ(t). The admissibility condition is directly related to the decay of the wavelet function ψ(t) which is required to have good localization. The admissibility condition for a continuous ψ(Ω) is equivalent to a zero-mean wavelet function in time:
68 This condition forces that the wavelet function is a band pass function and decays at least as fast as |t|^1-ε in time where e is some decay constant. (In practice one needs to have much faster decay of tit (t) , in order to have good time localization). The admissibility condition assures that the "resolution of the identity" holds [45]. This guarantees that any function f(t) E 1,2 (R^n) can be reconstructed from the wavelet space as where the wavelet coefficients were defined earlier in Eq. (3.63). Its mathematical proof is given in the references [45][46]. Whenever ψ(t) is a real function, the integral limits of Ch in Eq. (3.68) are changed from 0 to 00 . Resolution of the identity ensures that the continuous wavelet transform (CWT) is complete if W f (a,b) are known for all a and b. A continuous signal f(t) is represented by a pass band function ψ(t) and its dilated and translated versions. The dilation in time leads to different resolutions in frequency. ψ(t) is a prototype window and is normally referred to as the mother wavelet. The digital implementation of the CWT can be computed directly by convolving the signal with a scaled and dilated version of the mother wavelet. For a reasonably efficient implementation, an FFT may be applied to perform the convolution [46a]. In its discrete form, a = ao^j -=n 0-3where j • and n za are integers. This is referred to as the discrete wavelet transform (DWT), which is discussed in more detail in
- Page 45 and 46: 16 Figure 2.2 The systemic and pulm
- Page 47 and 48: 18 illustrated in Figure 2.3. The i
- Page 49 and 50: 20 2.2 Blood Pressure The force tha
- Page 51 and 52: 22 2.4 The Nervous System Human beh
- Page 53 and 54: 24 The sympathetic nerve fibers lea
- Page 55 and 56: 26 Without these sympathetic and pa
- Page 57 and 58: 28 center in the medulla, which con
- Page 59 and 60: 30 Figure 2.6 Autonomic innervation
- Page 61 and 62: 32 average heart rate was measured
- Page 63 and 64: 34 However, they do note that there
- Page 65 and 66: Figure 2.9 The placement of the pos
- Page 67 and 68: 38 female. While more men suffer fr
- Page 69 and 70: 40 Stage II: Moderate COPD - Worsen
- Page 71 and 72: CHAPTER 3 ENGINEERING BACKGROUND Th
- Page 73 and 74: 44 Two common types of time-frequen
- Page 75 and 76: 46 STFT: Short-Time Fourier Transfo
- Page 77 and 78: 48 3.3 The Analytic Signal and Inst
- Page 79 and 80: 50 The advantage of using equation
- Page 81 and 82: 52 3.5 Covariance and Invariance Th
- Page 83 and 84: where H(f), S(f) are Fourier transf
- Page 85 and 86: 56 Another shortcoming of the spect
- Page 87 and 88: 58 should take the kernel of the WD
- Page 89 and 90: 60 called the cross Wigner distribu
- Page 91 and 92: 62 3.6.3 The Choi-Williams (Exponen
- Page 93 and 94: 64 Figure 3.3 Performance of the Ch
- Page 95: 66 [-Ω,Ω ], then its STFT will be
- Page 99 and 100: 70 where c is a constant. Thus, the
- Page 101 and 102: Figure 3.5 The time-frequency plane
- Page 103 and 104: 74 The measure dadb used in the tra
- Page 105 and 106: 76 and the wavelet transform repres
- Page 107 and 108: 78 Figure 3.6 Figure depicting the
- Page 109 and 110: 80 The final step to obtain the pow
- Page 111 and 112: 82 It should be noted that if the w
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- Page 115 and 116: Figure 3.12 Power spectrum of BP II
- Page 117 and 118: RR similar manner to give: When com
- Page 119 and 120: 90 when there is significant correl
- Page 121 and 122: 92 3.12 Partial Coherence Analysis
- Page 123 and 124: 94 after removal of the effects of
- Page 125 and 126: 96 The bulk of the theory and appli
- Page 127 and 128: 98 technique is measurement time. T
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- Page 131 and 132: 102 variability exists in the propa
- Page 133 and 134: 104 eXogenous input (ARX) was used
- Page 135 and 136: 106 The baroreflex, an autonomic re
- Page 137 and 138: 108 the principal components are no
- Page 139 and 140: 110 The mathematical solution for t
- Page 141 and 142: 112 3.15 Cluster Analysis The term
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- Page 145 and 146: 116 3.15.5 Squared Euclidian Distan
68<br />
This condition forces that the wavelet function is a band pass function and<br />
decays at least as fast as |t|^1-ε in time where e is some decay constant. (In practice one<br />
needs to have much faster decay <strong>of</strong> tit (t) , in order to have good time localization).<br />
The admissibility condition assures that the "resolution <strong>of</strong> the identity" holds<br />
[45]. This guarantees that any function f(t) E 1,2 (R^n) can be reconstructed from the<br />
wavelet space as<br />
where the wavelet coefficients were defined earlier in Eq. (3.63). Its mathematical pro<strong>of</strong><br />
is given in the references [45][46]. Whenever ψ(t) is a real function, the integral limits<br />
<strong>of</strong> Ch in Eq. (3.68) are changed from 0 to 00 .<br />
Resolution <strong>of</strong> the identity ensures that the continuous wavelet transform (CWT)<br />
is complete if W f (a,b) are known for all a and b. A continuous signal f(t) is<br />
represented by a pass band function ψ(t) and its dilated and translated versions. The<br />
dilation in time leads to different resolutions in frequency. ψ(t) is a prototype window<br />
and is normally referred to as the mother wavelet. The digital implementation <strong>of</strong> the<br />
CWT can be computed directly by convolving the signal with a scaled and dilated<br />
version <strong>of</strong> the mother wavelet. For a reasonably efficient implementation, an FFT may<br />
be applied to perform the convolution [46a].<br />
In its discrete form, a = ao^j -=n 0-3where j • and n za<br />
are integers. This is<br />
referred to as the discrete wavelet transform (DWT), which is discussed in more detail in