Preprocessing for Extracting Signal Buried
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Abstract
Digital signals are used everywhere in the world around us due to its superior fidelity,
noise reduction, and signal processing flexibility to remove noise and extract useful
information. This unwanted electrical or electromechanical energy that distort the signal
quality is known as noise, it can block, distort change or interfere with the meaning of a
message in both human and electronic communication. Engineers are constantly striving
to develop better ways to deal with noise disturbances as it leads to loss of useful
information. The traditional method has been used to minimize the signal bandwidth to
the greatest possible extent. However reducing the bandwidth limits the maximum speed
of the data than can be delivered. Another, more recently developed scheme for
minimizing the effect of noise is called digital signal processing.
Digital filters are very much more versatile in their ability to process
signals in a variety of ways and can handle low frequency signals accurately; this
includes the ability of some types of digital filter to adapt to changes in the characteristics
of the signal. Fast DSP processors can handle complex combinations of filters in parallel
or cascade (series), making the hardware requirements relatively simple and compact in
comparison with the equivalent analog circuitry. In order to extract useful information
from the noisy signals, raw signal has to be processed. By analyzing and processing the
digital data, the useful information is obtained from the noise and present it in a form
more comprehensible than the raw data. The signal processing can be roughly divided
into two stages by functionality: preprocessing and feature extraction. The preprocessing
stage removes or suppresses noise from the raw signal and the feature extraction stage
extracts information from the signal. In this thesis the extraction of a signal i.e.
preprocessing is done by using LabVIEW which has extensive set of signal processing
VI’s that simplify the development of digital processing system for improved noise
reduction and efficient extraction of desired signal.
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