Paper PublishingAdaptive Channel Equalization
Abstract
In digital communications systems, data is transmitted from the transmitter to the receiver over a channel, which may be a cable or a wireless medium. Every physical channel adds some random noise to the transmitted signal, and so the received signal is a noisy version of the transmitted signal. In addition, the transmitted signal will be distorted if the frequency response of the channel is not flat and its phase response is not linear. The term channel equalization stems from the requirement that the amplitude response of the channel must be flat, that is, the same for all frequencies of the channel. If the amplitude response is not flat, it must be equalized using an appropriate device at the receiver, which is called an equalizer. Hence, we have implemented a comparison between two channel equalizers named as Training mode adaptive equalizer and blind mode adaptive equalizer. The results reveal the comparison between two equalizers.
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Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
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