M.Sc. Engg.

Browse

Search Results

Now showing 1 - 10 of 15
  • Thumbnail Image
    Item
    Design and Implementation of Sampling Rate Conversion System for Electroencephalogram (EEG) on FPGA Device
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-11) Hassan, Mahamudul; Islam, Prof. Dr. Sheikh Md. Rabiul
    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.
  • Thumbnail Image
    Item
    Cross-correlation based Acoustic Signal Processing Technique and its Implementation on Marine Ecology
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-12) Hossain, S. M. Asif; Hossen, Prof. Dr. Monir
    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.
  • Thumbnail Image
    Item
    Design and Analysis of a Pattern Reconfigurable Antenna for Wi-Fi Base Station
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-11) Islam, Md Nazmul; Rahman, Prof. Dr. Md. Mostafizur
    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.
  • Thumbnail Image
    Item
    Design a Multistage Multirate System for Atrial Fibrillation Detection using ECG Signal
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-11) Johura, Fatema Tuj; Islam, Prof. Dr. Sheikh Md. Rabiul
    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.
  • Thumbnail Image
    Item
    Brain Tumor Classification and Watermarking of MRI Using Nonsubsampled Contourlet Transform
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-11) Saha, Chandan; Hossain, Prof. Dr. Md. Foisal
    Automatic or semi-automatic brain tumor classification scheme is demanded in today’s medical system to get rid of human involvement of classification of brain tumor images. So, here we propose nonsubsampled contourlet transform (NSCT) based MRI brain tumor classification using support vector machine (SVM) and artificial neural network (ANN) classifier. In this scheme, K-means clustering is used for segmentation of region of interest. NSCT is applied to the region of interest of brain image in order to obtain its low and high subband coefficients. Then from the coefficients of NSCT, twelve features are extracted from the region of interest. SVM which incorporates two stages is trained with these twelve features. 1st stage of SVM is able to classify brain image as normal or abnormal and then 2nd stage of SVM classifies grade of tumor as low grade, where tumor is slowly growing or high grade, where tumor is rapidly growing. The grade of tumor is also classified using the ANN classifier based on feed forward back propagation. Furthermore, when the multimedia contents like MRIs or other images are transferred through a communication channel, sometimes the whole content or its part may be modified or deteriorated by hackers. In order to protect this content from unauthorized user, digital watermarking is considered to be a promising tool. So another purpose of this research is to develop image watermarking scheme which ensures higher security, imperceptibility and robustness against different distortion attacks. In first proposed scheme of image watermarking, NSCT is also used because most of the perceptual content of an image focuses on low frequency subband of NSCT. Singular value decomposition (SVD) is also applied on low frequency subband of NSCT, because the singular values taken from low frequency subband have certain stability. Besides, game of life (GOL) cellular automata is used to scramble binary watermark so that no one can recover the watermark without secret scrambling keys. So in this scheme, NSCT and SVD ensure the imperceptibility and robustness as well as cellular automata improves the security. In second proposed scheme of watermarking, multiple chaotic maps, NSCT and discrete cosine transform (DCT) are used. Here, an arranged chaotic sequence which is created by logistic map is used to shuffle the pixel positions of MRI. Patient information, watermark is encrypted by two chaotic maps, like Arnold’s Cat map and tent map. Then, DCT coefficients of encrypted watermark are embedded into the DCT coefficients of NSCT’s approximation band of shuffled MRI. Both proposed watermarking schemes are tested on varieties of MRIs and their associated results reveal that the two schemes have promising improvements in imperceptibility and robustness against noise and geometric attacks. Overall, NSCT is used in both brain tumor classification and watermarking in this research.
  • Thumbnail Image
    Item
    A Compressive Sensing Approach to Analyze the Performance of wideband Cognitive Radio Networks
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2018-04) Ahmmed, S. M. Bulbul; Alam, Prof. Dr. Sk. Shariful
    In the field of wireless communication systems, Cognitive Radio (CR) technology is the talk of the time for the best utilization of spread spectrum frequency. In the Wideband range, traditional Narrowband Sensing methods are not suitable to apply for performing Spectrum Sensing, as of making a single binary decision (Primary User present or absent) in the entire Wideband signal, thus cannot locate individual spectral opportunities that rely within the Wideband Spectrum. The Compressive Sensing (CS) can recover sparse signals at Sub-Nyquist rates and it depends on this principle of sparsity, so that a brief representation of the signal is possible when expressed in a suitable form. This research work has proposed a model of CR receiver sensing module which can be able to estimate a significant part (which is highly sparse among the segments of the spectrum) of the entire Wideband Spectrum with lower computational complexity. This propose work aims to analyze the compression ratio, i.e. M/N, with different number of Primary User (PUs) present in the wideband frequency from the Receiver Operating Characteristics (ROC) curves. Additionally, it is also analyzed that how the compression ratio, M/N characteristics varies with signal-t-noise ratio (SNR) in the wideband frequency from the ROC curves. This work investigates the probability of detection, Pd versus SNR for a fixed M/N and the throughput of a CR network against sensing period for a fixed frame length and vice versa. This proposed work also aims to find the requirement of less computational complexity and physical memory. Eventually, from the wide investigations through our proposed research work, it is found that the proposed method provides better throughput for fixed frame length as well as fixed sensing slot duration as well as frame duration the throughput is greater for shorter sensing time period. It can hopefully state in the final point that the proposed method proves its significance in CR system.
  • Thumbnail Image
    Item
    Analysis of In-band Transmission of Baseband and Broadcast Signals for Next Generation WDM-PON
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2017-12) Rumi, Shamima Nasrin; Choudhury, Prof. Dr. Pallab Kumar
    This research was conducted to deal with the problem of finding cost-effective solutions for Fiber-to-the-Home (FTTH) network deployment. In the FTTH network, the transceiver at the user premises and the deployment of fiber at the last mile are the major barriers. A novel approach is demonstrated for the ultimate solution to ensure large bandwidth, wavelength independency, easy upgradability and excellent network security. A single wavelength can be shared by both the baseband and broadcast data where the system utilizes the subcarrier multiplexing (SCM) signals for broadcasting service and finally combined with baseband data to modulate a single optical source. This approach simplifies the design of optical line terminal (OLT) and meets the future bandwidth demand. In this project work, a wavelength reuse bidirectional WDM-PON is proposed for the transmission of both baseband and broadcast data in single wavelength. Broadcasting signals are generated in different radio frequencies (RF) to meet the diverse applications in both residential and commercial networks. Since the broadcast signals are placed in-band to the baseband data, the propose system does not require additional bandwidth dedicated for broadcast transmission. Moreover, the combined signal is received by a single photodiode and recovers the corresponding data without any wavelength specific optical or electrical filter. Beside this, wavelength reuse architecture ensure maximum utilization of available wavelengths and simplify the 'colorless' operation of upstream/downstream transmission.
  • Thumbnail Image
    Item
    Tumor and Its Stages Detection in Brain MRI Using Template Based K-means and Fuzzy C-means Clustering Algorithm
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2016-01) Ahmmed, Rasel; Hossain, Dr. Md. Foisal
    Segmentation is obligatory process in medical application for MRI image to detect brain tumour. This research work represents a robust segmentation method which is the integration of Template based K-means and modified Fuzzy C-means (TKFCM) clustering computed algorithm that, reduces the lack of operator performance, and error in equipment. In this method, the template is selected based on convolution between grey level intensity in small portion of brain image, and brain tumour image. K-means algorithm is to emphasized initial segmentation through the proper selection of template. Updated membership of FCM is obtained through distances from cluster centroid to cluster data points, until it reaches to its best. This Euclidian distance depends upon the different features i.e. intensity, entropy, contrast, dissimilarity and homogeneity of coarse image, which was depended only on similarity in conventional FCM. Then, on the basis of updated membership and automatic cluster selection, a sharp segmented image is obtained with red marked tumour from modified FCM technique. The small deviation of grey level intensity of normal and abnormal tissue is detected through TKFCM. For the tumor and its stages classification the linearization and region properties algorithm is needed to apply on detected tumor obtained from TKFCM, which provides the characteristics parameters like area, eccentricity, bounding box, perimeters and orientation. By these parameters the classified tumor and its stages are extracted. Besides the performances of TKFCM method is analyzed through neural network not only mathematically but also graphically. The resultant values give a better regression and least error compare to the other existing methods. This method will also help in detecting tumor in multiple intensity based brain MRI image.
  • Thumbnail Image
    Item
    Theoretical Design of Surface Plasmon Resonance based Microwave Sensor using Optical Fiber
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2014-09) Khan, Imran; Rahman, Prof. Dr. Md. Mostafizur
    Microwaves (MW) sensing is done through a complex and large size sensor which comprises a lot of electronic components. In this research, microwave (MW) sensing, based on surface plasmon resonance using optical fiber is analyzed and a new scheme to sense MW is proposed. The motivation is to introduce a new scheme to sense MW, minimize the conventional MW detector size and reduce the number of electronic components in the sensor by using a new scheme. Here MW is detected by measuring the surface plasmon wavelength shift which is the result of the related Bragg wavelength shift (0.009 nm/ 0C ) in the optical fiber due to temperature change. The results are compared with existing research findings to establish the sensing principle of MW based on surface plasmon resonance, generated in optical fiber’s metal-dielectric interface. This proposed sensor can be integrated with other micro-electronic devices very easily.
  • Thumbnail Image
    Item
    Design of Symmetric 10 Gbps Bi-Directional Wavelength Reused Optical Access Networks
    (Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh., 2016-08) Khan, Tanvir Zaman; Choudhury, Dr. Pallab Kumar
    This research was conducted to deal with the problem of finding cost‐effective solutions for Fiber‐to‐the‐Home (FTTH) network deployment. In the FTTH network, the transceiver at the user premises and the deployment of fiber at the last mile are the major barriers. A novel approach is demonstrated for reducing the noise of residual modulation and Rayleigh backscattering (RB) in bidirectional single fiber wavelength division multiplexing passive optical network (WDM-PON) with 10 Gb/s symmetric differential phase shift keying (DPSK) signal in downstream (DS) and OFDM re-modulated signal in upstream (US). Centralized wavelength reused WDM-PON produces re-modulation noise and bidirectional single fiber generates RB noise. For simplicity, first approach only studied the effect of remodulation noise and the second approach is the final design of this thesis work. The first approach proposed a 10 Gb/s symmetric bidirectional dual fiber wavelength reuse WDM-PON with DPSK signal in DS and reflective semiconductor optical amplifier (RSOA) re-modulation with orthogonal frequency division multiplexing (OFDM) in US. RSOA is used for its colorless and cost effective property and dual fiber is used to avoid RB noise. Similarly, DPSK is used for its constant envelop (CE) property to reduce re-modulation noise. The results show that the proposed first approach can achieve good performance over 25 km fiber transmission with error free operation in DS and bit error rate (BER) lower than forward error correction (FEC) limit in US. But the dual fiber approach is not cost effective. It increases the use of optical resources and network size outside of the plan. Therefore, another approach of single fiber is also presented in this thesis. The second proposed approach is a 10 Gb/s symmetric bidirectional single fiber wavelength reuse WDM-PON with DPSK signal in DS and Mach-zhender modulator (MZM) remodulation with OFDM signal in US. MZM is used to overcome the bandwidth limitation to reach 10 Gb/s. But this scheme severely affected by RB noise. Because RB noise spectra overlaps with OFDM signal near the DC frequency. This in-band coherent noise severely degrades the system performance. To overcome this limitation, wavelength shifted approach is used to reduce the spectral overlap. It is found that by shifting only 375 MHz, system can achieve a significant improvement.