Search results for: Noise pollution
758 Method to Improve Channel Coding Using Cryptography
Authors: Ayyaz Mahmood
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A new approach for the improvement of coding gain in channel coding using Advanced Encryption Standard (AES) and Maximum A Posteriori (MAP) algorithm is proposed. This new approach uses the avalanche effect of block cipher algorithm AES and soft output values of MAP decoding algorithm. The performance of proposed approach is evaluated in the presence of Additive White Gaussian Noise (AWGN). For the verification of proposed approach, computer simulation results are included.Keywords: Advanced Encryption Standard (AES), Avalanche Effect, Maximum A Posteriori (MAP), Soft Input Decryption (SID).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1943757 Fuzzy Cost Support Vector Regression
Authors: Hadi Sadoghi Yazdi, Tahereh Royani, Mehri Sadoghi Yazdi, Sohrab Effati
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In this paper, a new version of support vector regression (SVR) is presented namely Fuzzy Cost SVR (FCSVR). Individual property of the FCSVR is operation over fuzzy data whereas fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown in the experimental results as a property of the proposed method and superiority relative conventional SVR.
Keywords: Support vector regression, Fuzzy input, Fuzzy cost.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1367756 Sustainable Energy Production with Closed-Loop Methods: Evaluating the Influence of Power Plant Age on Production Efficiency and Environmental Impact
Authors: Bujar Ismaili, Bahti Ismajli, Venhar Ismaili, Skender Ramadani
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In Kosovo, the problem with the electricity supply is huge and it does not meet the demands of consumers. Older thermal power plants, which are regarded as big environmental polluters, produce most of the energy. Our experiment is based on the production of electricity using the closed method that does not affect environmental pollution by using waste as fuel that is considered to pollute the environment. The experiment was carried out in the village of Godanc, municipality of Shtime, Kosovo. In the experiment, a production line based on the production of electricity and central heating was designed at the same time. The results are the benefits of electricity as well as the release of temperature for heating with minimal expenses and with the release of 0% gases into the atmosphere. During this experiment, coal, plastic, waste from wood processing, and agricultural wastes were used as raw materials. The method utilized in the experiment allows for the release of gas through pipes and filters during the top-to-bottom combustion of the raw material in the boiler, followed by the method of gas filtration from waste wood processing (sawdust). During this process, the final product, gas, is obtained. This gas passes through the carburetor, enabling the combustion process to put the internal combustion machine and the generator into operation and produce electricity that does not release gases into the atmosphere. The results show that the system provides energy stability without environmental pollution from toxic substances and waste, as well as with low production costs. From the final results, it follows that, in the case of using coal fuel, we have benefited from more electricity and higher temperature release, followed by plastic waste, which also gave good results. The results obtained during these experiments prove that the current problems of lack of electricity and heating can be met at a lower cost and have a clean environment and waste management.
Keywords: Energy, heating, atmosphere, waste management, gasification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 212755 GPS Signal Correction to Improve Vehicle Location during Experimental Campaign
Authors: L. Della Ragione, G. Meccariello
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In recent years in Italy the progress of the automobile industry, in the field of reduction of emissions values, is very remarkable. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. In this paper we dealt with the problem of describing a quantitatively approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars.
Keywords: Air pollution, Driving cycles, GPS signal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1909754 An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System
Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa
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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1871753 Hardware Centric Machine Vision for High Precision Center of Gravity Calculation
Authors: Xin Cheng, Benny Thörnberg, Abdul Waheed Malik, Najeem Lawal
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We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.Keywords: Dynamic thresholding, segmentation, position measurement, sub-pixel precision, center of gravity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2347752 Analysis of Combined Use of NN and MFCC for Speech Recognition
Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam
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The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.
Keywords: Speech Recognition, MFCC, Neural Network, classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3263751 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments
Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic
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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.
Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1564750 Backplane Serial Signaling and Protocol for Telecom Systems
Authors: Ali Poureslami, Hossein Borhanifar, Seyed Ali Alavian
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In this paper, we implement a modern serial backplane platform for telecommunication inter-rack systems. For combination high reliability and low cost protocol property, we applied high level data link control (HDLC) protocol with low voltage differential signaling (LVDS) bus for card to card communicated over backplane. HDLC protocol is a high performance with several operation modes and is famous in telecommunication systems. LVDS bus is a high reliability with high immunity against electromagnetic interference (EMI) and noise.Keywords: Backplane, BLVDS, HDLC, EMI, I2C, LCT, OSC, SFP, SNMP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2265749 Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel
Authors: Said Elkassimi, Said Safi, B. Manaut
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This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.
Keywords: Adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2117748 Alternative to M-Estimates in Multisensor Data Fusion
Authors: Nga-Viet Nguyen, Georgy Shevlyakov, Vladimir Shin
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To solve the problem of multisensor data fusion under non-Gaussian channel noise. The advanced M-estimates are known to be robust solution while trading off some accuracy. In order to improve the estimation accuracy while still maintaining the equivalent robustness, a two-stage robust fusion algorithm is proposed using preliminary rejection of outliers then an optimal linear fusion. The numerical experiments show that the proposed algorithm is equivalent to the M-estimates in the case of uncorrelated local estimates and significantly outperforms the M-estimates when local estimates are correlated.Keywords: Data fusion, estimation, robustness, M-estimates.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1826747 Performance Evaluation of Music and Minimum Norm Eigenvector Algorithms in Resolving Noisy Multiexponential Signals
Authors: Abdussamad U. Jibia, Momoh-Jimoh E. Salami
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Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
Keywords: Eigenvector, minimum norm, multiexponential, subspace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1734746 Sigma-Delta ADCs Converter a Study Case
Authors: Thiago Brito Bezerra, Mauro Lopes de Freitas, Waldir Sabino da Silva Júnior
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The Sigma-Delta A/D converters have been proposed as a practical application for A/D conversion at high rates because of its simplicity and robustness to imperfections in the circuit, also because the traditional converters are more difficult to implement in VLSI technology. These difficulties with conventional conversion methods need precise analog components in their filters and conversion circuits, and are more vulnerable to noise and interference. This paper aims to analyze the architecture, function and application of Analog-Digital converters (A/D) Sigma-Delta to overcome these difficulties, showing some simulations using the Simulink software and Multisim.
Keywords: Analysis, Oversampling Modulator, A/D converters, Sigma-Delta.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2680745 A Direct Down-conversion Receiver for Low-power Wireless Sensor Networks
Authors: Gianluca Cornetta, Abdellah Touhafi, David J. Santos, Jose Manuel Vazquez
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A direct downconversion receiver implemented in 0.13 μm 1P8M process is presented. The circuit is formed by a single-end LNA, an active balun for conversion into balanced mode, a quadrature double-balanced passive switch mixer and a quadrature voltage-controlled oscillator. The receiver operates in the 2.4 GHz ISM band and complies with IEEE 802.15.4 (ZigBee) specifications. The circuit exhibits a very low noise figure of only 2.27 dB and dissipates only 14.6 mW with a 1.2 V supply voltage and is hence suitable for low-power applications.
Keywords: LNA, Active Balun, Passive Mixer, VCO, IEEE 802.15.4(ZigBee).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2345744 Optimum Cascaded Design for Speech Enhancement Using Kalman Filter
Authors: T. Kishore Kumar
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Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1728743 Photovoltaic Array Sizing for PV-Electrolyzer
Authors: Panhathai Buasri
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Hydrogen that used as fuel in fuel cell vehicles can be produced from renewable sources such as wind, solar, and hydro technologies. PV-electrolyzer is one of the promising methods to produce hydrogen with zero pollution emission. Hydrogen production from a PV-electrolyzer system depends on the efficiency of the electrolyzer and photovoltaic array, and sun irradiance at that site. In this study, the amount of hydrogen is obtained using mathematical equations for difference driving distance and sun peak hours. The results show that the minimum of 99 PV modules are used to generate 1.75 kgH2 per day for two vehicles.Keywords: About four key words or phrases in alphabetical order, separated by commas.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1745742 Limits of Phase Modulated Frequency Shifted Holographic Vibrometry at Low Amplitudes of Vibrations
Authors: Pavel Psota, Vít Lédl, Jan Václavík, Roman Doleček, Pavel Mokrý, Petr Vojtíšek
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This paper presents advanced time average digital holography by means of frequency shift and phase modulation. This technique can measure amplitudes of vibrations at ultimate dynamic range while the amplitude distribution evaluation is done independently in every pixel. The main focus of the paper is to gain insight into behavior of the method at low amplitudes of vibrations. In order to reach that, a set of experiments was performed. Results of the experiments together with novel noise suppression show the limit of the method to be below 0.1 nm.Keywords: Acousto-optical modulator, digital holography, low amplitudes, vibrometry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1114741 A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems
Authors: Keunhong Chae, Seokho Yoon
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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.
Keywords: Code acquisition, optical CDMA, optical orthogonal code, serial algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2152740 A 1.5V,100MS/s,12-bit Current-Mode CMOSS ample-and-Hold Circuit
Authors: O. Hashemipour, S. G. Nabavi
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A high-linearity and high-speed current-mode sampleand- hold circuit is designed and simulated using a 0.25μm CMOS technology. This circuit design is based on low voltage and it utilizes a fully differential circuit. Due to the use of only two switches the switch related noise has been reduced. Signal - dependent -error is completely eliminated by a new zero voltage switching technique. The circuit has a linearity error equal to ±0.05μa, i.e. 12-bit accuracy with a ±160 μa differential output - input signal frequency of 5MHZ, and sampling frequency of 100 MHZ. Third harmonic is equal to –78dB.Keywords: Zero-voltage-technique, MOS-resistor, OTA, Feedback-resistor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1403739 Quantitative Analysis of PCA, ICA, LDA and SVM in Face Recognition
Authors: Liton Jude Rozario, Mohammad Reduanul Haque, Md. Ziarul Islam, Mohammad Shorif Uddin
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Face recognition is a technique to automatically identify or verify individuals. It receives great attention in identification, authentication, security and many more applications. Diverse methods had been proposed for this purpose and also a lot of comparative studies were performed. However, researchers could not reach unified conclusion. In this paper, we are reporting an extensive quantitative accuracy analysis of four most widely used face recognition algorithms: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) using AT&T, Sheffield and Bangladeshi people face databases under diverse situations such as illumination, alignment and pose variations.
Keywords: PCA, ICA, LDA, SVM, face recognition, noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2426738 Frequency Estimation Using Analytic Signal via Wavelet Transform
Authors: Sudipta Majumdar, Akansha Singh
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Frequency estimation of a sinusoid in white noise using maximum entropy power spectral estimation has been shown to be very sensitive to initial sinusoidal phase. This paper presents use of wavelet transform to find an analytic signal for frequency estimation using maximum entropy method (MEM) and compared the results with frequency estimation using analytic signal by Hilbert transform method and frequency estimation using real data together with MEM. The presented method shows the improved estimation precision and antinoise performance.Keywords: Frequency estimation, analytic signal, maximum entropy method, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1733737 Sociological Impact on Education An Analytical Approach Through Artificial Neural network
Authors: P. R. Jayathilaka, K.L. Jayaratne, H.L. Premaratne
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This research presented in this paper is an on-going project of an application of neural network and fuzzy models to evaluate the sociological factors which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool which helps these students for a better performance at their examinations, especially at their G.C.E O/L (General Certificate of Education-Ordinary Level) examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize the performance patterns against the chosen social factors.Keywords: Education, Fuzzy, neural network, prediction, Sociology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1635736 A 3rd order 3bit Sigma-Delta Modulator with Reduced Delay Time of Data Weighted Averaging
Authors: Soon Jai Yi, Sun-Hong Kim, Hang-Geun Jeong, Seong-Ik Cho
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This paper presents a method of reducing the feedback delay time of DWA(Data Weighted Averaging) used in sigma-delta modulators. The delay time reduction results from the elimination of the latch at the quantizer output and also from the falling edge operation. The designed sigma-delta modulator improves the timing margin about 16%. The sub-circuits of sigma-delta modulator such as SC(Switched Capacitor) integrator, 9-level quantizer, comparator, and DWA are designed with the non-ideal characteristics taken into account. The sigma-delta modulator has a maximum SNR (Signal to Noise Ratio) of 84 dB or 13 bit resolution.Keywords: Sigma-delta modulator, multibit, DWA
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2399735 Recognition of Isolated Speech Signals using Simplified Statistical Parameters
Authors: Abhijit Mitra, Bhargav Kumar Mitra, Biswajoy Chatterjee
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We present a novel scheme to recognize isolated speech signals using certain statistical parameters derived from those signals. The determination of the statistical estimates is based on extracted signal information rather than the original signal information in order to reduce the computational complexity. Subtle details of these estimates, after extracting the speech signal from ambience noise, are first exploited to segregate the polysyllabic words from the monosyllabic ones. Precise recognition of each distinct word is then carried out by analyzing the histogram, obtained from these information.Keywords: Isolated speech signals, Block overlapping technique, Positive peaks, Histogram analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1422734 Forces Association-Based Active Contour
Authors: Aicha Baya Goumeidane, Nafaa. Nacereddine
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A welded structure must be inspected to guarantee that the weld quality meets the design requirements to assure safety and reliability. However, X-ray image analyses and defect recognition with the computer vision techniques are very complex. Most difficulties lie in finding the small, irregular defects in poor contrast images which requires pre processing to image, extract, and classify features from strong background noise. This paper addresses the issue of designing methodology to extract defect from noisy background radiograph with image processing. Based on the use of actives contours this methodology seems to give good results
Keywords: Welding, Radiography, Computer vision, Active contour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1882733 Robust Probabilistic Online Change Detection Algorithm Based On the Continuous Wavelet Transform
Authors: Sergei Yendiyarov, Sergei Petrushenko
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In this article we present a change point detection algorithm based on the continuous wavelet transform. At the beginning of the article we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that we describe a probabilistic algorithm which can be used to find changes using our transformed signal. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.
Keywords: Change detection, sinter production, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1455732 Efficient Realization of an ADFE with a New Adaptive Algorithm
Authors: N. Praveen Kumar, Abhijit Mitra, C. Ardil
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Decision feedback equalizers are commonly employed to reduce the error caused by intersymbol interference. Here, an adaptive decision feedback equalizer is presented with a new adaptation algorithm. The algorithm follows a block-based approach of normalized least mean square (NLMS) algorithm with set-membership filtering and achieves a significantly less computational complexity over its conventional NLMS counterpart with set-membership filtering. It is shown in the results that the proposed algorithm yields similar type of bit error rate performance over a reasonable signal to noise ratio in comparison with the latter one.Keywords: Decision feedback equalizer, Adaptive algorithm, Block based computation, Set membership filtering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1671731 Implementation of Technology Concept for the Reduction of Cyanobacteria in Laboratory
Authors: D. Šebo, M. Fedorčáková
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Following the research in the Department of environmental engineering in Faculty of mechanical engineering on Technical University of Kosice and experiences with electrocoagulation style of disposal waste water, there were designed and partly examining the equipment of two stage revitalization on the standing and little fusible water of tenet electrolysis on the little tarns. With the cooperation with vet experts was that manners prove and it is innocuous for animals, during which time cyanobacteria are totally paralyzed. For the implementation of science and research results have been obtained by means EU funds for structural development.
Keywords: Cyanobacteria, Equipment, Pollution, Stagnant Water, Technology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1326730 Microcontroller Based EOG Guided Wheelchair
Authors: Jobby K. Chacko, Deepu Oommen, Kevin K. Mathew, Noble Sunny, N. Babu
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A new cost effective, eye controlled method was introduced to guide and control a wheel chair for disable people, based on Electrooculography (EOG). The guidance and control is effected by eye ball movements within the socket. The system consists of a standard electric wheelchair with an on-board microcontroller system attached. EOG is a new technology to sense the eye signals for eye movements and these signals are captured using electrodes, signal processed such as amplification, noise filtering, and then given to microcontroller which drives the motors attached with wheel chair for propulsion. This technique could be very useful in applications such as mobility for handicapped and paralyzed persons.
Keywords: Electrooculography, Microcontroller, Signal processing, Wheelchair.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5593729 Vibration Base Identification of Impact Force Using Genetic Algorithm
Authors: R. Hashemi, M.H.Kargarnovin
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This paper presents the identification of the impact force acting on a simply supported beam. The force identification is an inverse problem in which the measured response of the structure is used to determine the applied force. The identification problem is formulated as an optimization problem and the genetic algorithm is utilized to solve the optimization problem. The objective function is calculated on the difference between analytical and measured responses and the decision variables are the location and magnitude of the applied force. The results from simulation show the effectiveness of the approach and its robustness vs. the measurement noise and sensor location.Keywords: Genetic Algorithm, Inverse problem, Optimization, Vibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1548