M.Sc. Engg.
http://hdl.handle.net/20.500.12228/60
2024-03-29T04:43:54ZDesign and Implementation of Sampling Rate Conversion System for Electroencephalogram (EEG) on FPGA Device
http://hdl.handle.net/20.500.12228/499
Design and Implementation of Sampling Rate Conversion System for Electroencephalogram (EEG) on FPGA Device
Hassan, Mahamudul
The wide scale use of digital communication and digital media has made the necessity of methods
to process digital data more important now-a-days. The signal-rate system in digital signal
processing has evolved the key of fastest speed in digital signal processor. Field Programmable
Gate Array (FPGA) offers good solution for addressing the needs of high-performance DSP
systems. This concept leads to a chip with attractive features like, low requirements for the
coefficient word lengths, significant saving in computation and storage requirements results in a
significant reduction in its dynamic power consumption. There are many algorithms have been
proposed for processing of biomedical signal. Main objectives of these algorithm are to minimize
noise and artifacts existing with these signals, so that it will be easy to analyze and diagnosis
human diseases. The proposed system has many advantages on signal processing such that it has
a simple structure, stationary response and adaptively with embedded microprocessors. The system
is proposed due to facilitate structural characteristic and design properties on filtering EEG signal.
The focus of this project is on the basic DSP functions, namely filtering signals to remove
unwanted frequency using Sampling Rate Conversion (SRC) in digital signal processing. The
system has a computer where the design can be programmed and simulated on Xilinx
@
Integrated
Software Environment (ISE) Suite 14.7 or Quartus II software with interface ALTRA Cyclone DE
II board of FPGA device.
This thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Engineering in Electronics and Communication Engineering, November 2018.; Cataloged from PDF Version of Thesis.; Includes bibliographical references in each chapter.
2018-11-01T00:00:00ZCross-correlation based Acoustic Signal Processing Technique and its Implementation on Marine Ecology
http://hdl.handle.net/20.500.12228/494
Cross-correlation based Acoustic Signal Processing Technique and its Implementation on Marine Ecology
Hossain, S. M. Asif
As a scientific study of marine-life habitation, populations, and interactions among organisms and surrounding environment, marine ecology includes numerous fish and mammals as part and parcel. Marine fish and mammals have an enormous impact on marine ecosystems. Not only for their ecological values, but also for commercial purposes, a proper estimation of their population size is necessary. Besides, an efficient monitoring of populations and communities is the precondition of ecosystem-based management in marine areas. Most conventional techniques for estimating fish population are visual sampling techniques, environmental DNA (eDNA) technique, minnow traps, removal method of population estimation, echo integration techniques, etc., which are sometimes complex, costly, require human interaction, and harmful for inhabitation of marine species. In order to overcome these difficulties, an acoustic signal processing technique is proposed in this thesis. The method is based on a novel statistical signal processing technique called “cross-correlation” and different types of acoustic signals produced by diverse species of marine fish and mammals, like chirps, grunts, growls, clicks, etc. Our goal was to build a framework so that the technique can be implemented in practice. Therefore, we have investigated different tasks, which are crucial during its practical implementation like estimation with respect to different fish acoustics, different number of sensors and different distributions of fish and mammals. Similarly, we have carried an investigation to select the optimum estimation parameter for the technique. We have also analyzed different impacts, i.e., underwater bandwidth, SNR, etc., which have significant effects on practical estimation of this technique. From this research, we have found that chirp signals can produce better estimation results among the three fish acoustics, i.e., chirps, grunts, and growls signals. Among the three fish distributions, i.e., Exponential, Normal, and Rayleigh, Exponential distribution of fish and mammals produce better results. An increasing number of acoustic sensors provide better results in this technique. However, limited bandwidth of underwater channel poses a barrier during acquisition of fish signals, which has infinite bandwidth. To overcome this problem, a proper scaling is a mandatory task. We find that scaling factor 0.59512 for chirp signal and 0.55245 for grunt signal at 5 kHz underwater bandwidth. Similarly, a low signal to noise ratio (SNR) is also an impediment to obtain an accurate fish population. We have found that estimation with minimum SNR of 20 can perform like the noiseless estimation. These findings will immensely help the future researchers during practical implementation of the technique.
This thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Engineering in Electronics and Communication Engineering, December 2018.; Cataloged from PDF Version of Thesis.; Includes bibliographical references in each chapter.
2018-12-01T00:00:00ZDesign and Analysis of a Pattern Reconfigurable Antenna for Wi-Fi Base Station
http://hdl.handle.net/20.500.12228/489
Design and Analysis of a Pattern Reconfigurable Antenna for Wi-Fi Base Station
Islam, Md Nazmul
A unique concept for design of a pattern reconfigurable antenna and its simulation using
CST-MW simulator is presented in this research. The proposed design is a special type of
patch antenna and capable to make coverage at two directions without changing any common
properties of a typical antenna. This antenna is able to reconfigure the beam pattern
automatically, by using a pair of waveguide port without using any type of switching
mechanism. The proposed antenna is able to switch the radiation beam from one direction to
its 1800 reverse angle without changing its operating frequency that is 2.4 GHz. Besides, Wi-
Fi technology is the most popular and widely accepted WLAN (wireless local area network)
that operated at 2.4 GHz. So, this proposed antenna may have been easily adopted by Wi-Fi
(wireless fidelity) technology. This antenna provides wider bandwidth that is 455 MHz. This
enormous bandwidth makes the speed of data flow at higher rate along the WLAN, that’s the
more advantageous for designing a base station. The CST simulator carried out the simulated
result of return loss is -24.5 dB that is acceptable for telecommunication transmitter or
receiver. It covers the region of 480 to 1310 and 2280 to 3120 in azimuth plane. The footprint
of the radiation beam pattern is 820 (3dB points) for both ports. The beam of the antenna
focuses at these directions with directivity of 1.8 dBi. The simulated VSWR (voltage
standing wave ratio) value of antenna is 1.12 for both ports that can be chosen able for
wireless communication technology. It’s compactness in size and fabrication simplicity are
the attracting features for the base station designer. Thus, this proposed antenna can be easily
embedded in Wi-Fi system.
This thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Engineering in Electronics and Communication Engineering, November 2018.; Cataloged from PDF Version of Thesis.; Includes bibliographical references (pages 70-73).
2018-11-01T00:00:00ZDesign a Multistage Multirate System for Atrial Fibrillation Detection using ECG Signal
http://hdl.handle.net/20.500.12228/482
Design a Multistage Multirate System for Atrial Fibrillation Detection using ECG Signal
Johura, Fatema Tuj
Atrial Fibrillation (AF) is one of the most common cardiac arrhythmias. The number of patients related to heart failure due to AF is increasing day by day. Early detection of AF may reduce the risk of death due to heart failure. So, it has become more important to detect AF. There are various method to detect AF. In this thesis, we use ECG signal for AF detection. The MIT-BIH Atrial Fibrillation database is used to import ECG data for analysis. Filtered ECG signal using multistage multirate system for removing noise. RR interval of the ECG signal is calculated. Here we use the algorithm that mainly follows statistical method for detection of AF. Parametric statistic RMSSD and SE, and non-parametric statistic, TPR are used for this purpose. MATLAB R2016a is used to measure the values of those parameters for estimation of AF. The threshold values of RMSSD/ (Mean RR) taken from the literature is 0.1, SE is 0.7 and TPR is greater than 0.54 and lesser than 0.77. The resultant values of RMSSD, SE and TPR of every beat are checked weather it crosses the threshold level or not. If all the three parameters cross the threshold level then the beat flagged as AF. It shows excellent result when compared with the annotations of the database, and then the sensitivity, specificity and accuracy are determined. The algorithm has the sensitivity of 98.03%, specificity of 98.80% and accuracy of 99.45%. Thus, the result obtained in this study is appreciable compared to the other study found in literature.
This thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of
Master of Engineering (M.Sc. Eng.) in Electronics and Communication Engineering, November 2018.; Cataloged from PDF Version of Thesis.; Includes bibliographical references in each chapter.
2018-11-01T00:00:00Z