Difference between wavelet transform and fourier transform
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A filter is an electrical network that transmits signals within a specified frequency range called the pass band, and suppresses signals in the stop band, separated by the cut-off frequency. Digital filters are used to eliminate noise and extract signals of interest, implemented using software rather than RLC components. Digital filters are FIR (finite impulse response) or IIR (infinite impulse response) depending on the number of sample points used. An ideal filter would transmit signals in the pass band without attenuation and completely suppress the stop band, but ideal filters cannot be realized. IIR filter design first develops an analog IIR filter, then converts it to digital using methods like impulse invariant, approximation of derivatives, or bilinear transformation.
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The common area A is given by:
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A = 0 for d ≥ a
So the coupling efficiency η is given by:
η = A/πa2 = (1 - (d/a)2) for d < a
= 0 for d ≥ a
This shows that coupling efficiency decreases quadratically with offset d.
Even a small offset can cause significant power loss. Precise alignment is critical.
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In communication system, intersymbol interference (ISI) is a form of distortion of a signal in which one symbol interferes with subsequent symbols. This is an unwanted phenomenon as the previous symbols have similar effect as noise, thus making the communication less reliable.
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3) The document discusses the working, operation, and S-matrix of a magic tee. It also provides examples of how magic tees can be used for applications like impedance measurement, duplexing, and mixing.
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This document discusses voltage standing wave ratio (VSWR) meters, which are used to measure impedance matching and standing waves in microwave systems. It describes the principles of VSWR meters, including their construction with normal, expanded, and dB scales. Two common types are directional VSWR meters and SWR bridge circuits. Applications include laboratories, live broadcast systems, and medical equipment. Problems with VSWR meters are also noted, such as their inability to measure reactance and sensitivity to signal attenuation.
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This presentation covers:
Some basic definitions & concepts of digital communication
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Advantages & Disadvantages of BPSK
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Introduction .
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Applications of MSAs .
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Foc ppt
The common area A is given by:
A = π(a2 - (a - d)2) for d < a
A = 0 for d ≥ a
So the coupling efficiency η is given by:
η = A/πa2 = (1 - (d/a)2) for d < a
= 0 for d ≥ a
This shows that coupling efficiency decreases quadratically with offset d.
Even a small offset can cause significant power loss. Precise alignment is critical.
Irfan khan
Angular misalignment
- Angular misalignment occurs when the axes of the two fibers are not
perfectly parallel.
Discrete Fourier Transform
This document summarizes key aspects of the discrete Fourier transform (DFT). It defines the DFT, provides the formula for calculating it, and explains that the DFT transforms a discrete-time signal from the time domain to the frequency domain. It also outlines several important properties of the DFT, including linearity, shift property, duality, symmetry, and circular convolution. Examples are provided to illustrate duality and symmetry. References for further information on the discrete Fourier transform are also included.
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Histogram Equalization
Histogram Matching
Local Histogram processing
Using histogram statistics for image enhancement
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Histogram Equalization
Histogram Matching
Local Histogram Processing
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This document discusses image histogram equalization. It begins by defining an image histogram as a graphical representation of the number of pixels at each intensity value. Histogram equalization automatically determines a transformation function to produce a new image with a uniform histogram and increased contrast. This technique works by mapping the intensity values of the input image to a new range of values such that the histogram of the output image is uniform. The document provides an example of performing histogram equalization on an image and assigns related homework on digital image processing applications.
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The main advantage of wavelet transforms are
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2. Better Spectral localization properity
What is Multiresolution properity:
Multiresolution properity means that wavelet transform used different Scales for the analysis of different frequency componants of any signal .
What is scale:
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large scale is used for the analysis of small frequency componants presents in any signal Whereas Small scale is used for the analysis of high frequency componants of any signal
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Fourier Transform ,Time Domain representation of the signal
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