Search results for: Graph signal processing
2523 A Study and Implementation of On-line Learning Diagnosis and Inquiry System
Authors: YuLung Wu
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In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.Keywords: Knowledge Structure Graph, On-line LearningDiagnosis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14512522 EMD-Based Signal Noise Reduction
Authors: A.O. Boudraa, J.C. Cexus, Z. Saidi
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This paper introduces a new signal denoising based on the Empirical mode decomposition (EMD) framework. The method is a fully data driven approach. Noisy signal is decomposed adaptively into oscillatory components called Intrinsic mode functions (IMFs) by means of a process called sifting. The EMD denoising involves filtering or thresholding each IMF and reconstructs the estimated signal using the processed IMFs. The EMD can be combined with a filtering approach or with nonlinear transformation. In this work the Savitzky-Golay filter and shoftthresholding are investigated. For thresholding, IMF samples are shrinked or scaled below a threshold value. The standard deviation of the noise is estimated for every IMF. The threshold is derived for the Gaussian white noise. The method is tested on simulated and real data and compared with averaging, median and wavelet approaches.
Keywords: Empirical mode decomposition, Signal denoisingnonstationary process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39752521 A Hyper-Domain Image Watermarking Method based on Macro Edge Block and Wavelet Transform for Digital Signal Processor
Authors: Yi-Pin Hsu, Shin-Yu Lin
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In order to protect original data, watermarking is first consideration direction for digital information copyright. In addition, to achieve high quality image, the algorithm maybe can not run on embedded system because the computation is very complexity. However, almost nowadays algorithms need to build on consumer production because integrator circuit has a huge progress and cheap price. In this paper, we propose a novel algorithm which efficient inserts watermarking on digital image and very easy to implement on digital signal processor. In further, we select a general and cheap digital signal processor which is made by analog device company to fit consumer application. The experimental results show that the image quality by watermarking insertion can achieve 46 dB can be accepted in human vision and can real-time execute on digital signal processor.
Keywords: watermarking, digital signal processor, embedded system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12372520 All-Pairs Shortest-Paths Problem for Unweighted Graphs in O(n2 log n) Time
Authors: Udaya Kumar Reddy K. R, K. Viswanathan Iyer
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Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).
Keywords: Distance in graphs, Dynamic programming, Graphalgorithms, Shortest paths.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36782519 Altered Network Organization in Mild Alzheimer's Disease Compared to Mild Cognitive Impairment Using Resting-State EEG
Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan
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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.
Keywords: EEG, functional connectivity, graph theory, TFCMI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24932518 Improved Processing Speed for Text Watermarking Algorithm in Color Images
Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari
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Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.
Keywords: Steganography, watermarking, private keys, time complexity measurements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8092517 Empirical Mode Decomposition Based Denoising by Customized Thresholding
Authors: Wahiba Mohguen, Raïs El’hadi Bekka
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This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).
Keywords: Customized thresholding, ECG signal, EMD, hard thresholding, Soft-thresholding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10722516 Angle of Arrival Estimation Using Maximum Likelihood Method
Authors: H. K. Hwang, Zekeriya Aliyazicioglu, Solomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr
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Multiple-input multiple-output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection,resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO uniformly-spaced linear array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, pseudo random (PN) sequence length, number of snapshots, and signal to noise ratio (SNR). The results of MIMO are compared to a traditional array antenna.
Keywords: Multiple-input multiple-output (MIMO) radar, phased array antenna, target detection, radar signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27982515 Spread Spectrum Image Watermarking for Secured Multimedia Data Communication
Authors: Tirtha S. Das, Ayan K. Sau, Subir K. Sarkar
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Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.
Keywords: Spread spectrum modulation, spreading code, signaldecomposition, security, successive bit cancellation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27712514 Processing the Medical Sensors Signals Using Fuzzy Inference System
Authors: S. Bouharati, I. Bouharati, C. Benzidane, F. Alleg, M. Belmahdi
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Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.Keywords: Sensors, Sensivity, fuzzy logic, analysis, physiological parameters, medical diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19572513 Learning FCM by Tabu Search
Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mostafa Jafari, Salman Hooshmand
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Fuzzy Cognitive Maps (FCMs) is a causal graph, which shows the relations between essential components in complex systems. Experts who are familiar with the system components and their relations can generate a related FCM. There is a big gap when human experts cannot produce FCM or even there is no expert to produce the related FCM. Therefore, a new mechanism must be used to bridge this gap. In this paper, a novel learning method is proposed to construct causal graph based on historical data and by using metaheuristic such Tabu Search (TS). The efficiency of the proposed method is shown via comparison of its results of some numerical examples with those of some other methods.
Keywords: Fuzzy Cognitive Map (FCM), Learning, Meta heuristic, Genetic Algorithm, Tabu search.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18542512 Coherence Analysis between Respiration and PPG Signal by Bivariate AR Model
Authors: Yue-Der Lin, Wei-Ting Liu, Ching-Che Tsai, Wen-Hsiu Chen
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PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
Keywords: Coherence analysis, photoplethysmography (PPG), bivariate AR spectral estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25832511 Sperm Whale Signal Analysis: Comparison using the Auto Regressive model and the Daubechies 15 Wavelets Transform
Authors: Olivier Adam, Maciej Lopatka, Christophe Laplanche, Jean-François Motsch
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This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.Keywords: Autoregressive model, Daubechies Wavelet, Fourier Transform, marine mammals, signal processing, spectrogram, sperm whale, Wavelet Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19892510 In Vitro Study of Coded Transmission in Synthetic Aperture Ultrasound Imaging Systems
Authors: Ihor Trots, Yuriy Tasinkevych, Andrzej Nowicki, Marcin Lewandowski
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In the paper the study of synthetic transmit aperture method applying the Golay coded transmission for medical ultrasound imaging is presented. Longer coded excitation allows to increase the total energy of the transmitted signal without increasing the peak pressure. Moreover signal-to-noise ratio and penetration depth are improved while maintaining high ultrasound image resolution. In the work the 128-element linear transducer array with 0.3 mm inter-element spacing excited by one cycle and the 8 and 16- bit Golay coded sequences at nominal frequency 4 MHz was used. To generate a spherical wave covering the full image region a single element transmission aperture was used and all the elements received the echo signals. The comparison of 2D ultrasound images of the tissue mimicking phantom and in vitro measurements of the beef liver is presented to illustrate the benefits of the coded transmission. The results were obtained using the synthetic aperture algorithm with transmit and receive signals correction based on a single element directivity function.Keywords: Golay coded sequences, radiation pattern, signal processing, synthetic aperture, ultrasound imaging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16652509 Fault Detection and Diagnosis of Broken Bar Problem in Induction Motors Base Wavelet Analysis and EMD Method: Case Study of Mobarakeh Steel Company in Iran
Authors: M. Ahmadi, M. Kafil, H. Ebrahimi
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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.
Keywords: Broken bar, condition monitoring, diagnostics, empirical mode decomposition, Fourier transform, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7852508 Anonymous Editing Prevention Technique Using Gradient Method for High-Quality Video
Authors: Jiwon Lee, Chanho Jung, Si-Hwan Jang, Kyung-Ill Kim, Sanghyun Joo, Wook-Ho Son
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Since the advances in digital imaging technologies have led to development of high quality digital devices, there are a lot of illegal copies of copyrighted video content on the Internet. Also, unauthorized editing is occurred frequently. Thus, we propose an editing prevention technique for high-quality (HQ) video that can prevent these illegally edited copies from spreading out. The proposed technique is applied spatial and temporal gradient methods to improve the fidelity and detection performance. Also, the scheme duplicates the embedding signal temporally to alleviate the signal reduction caused by geometric and signal-processing distortions. Experimental results show that the proposed scheme achieves better performance than previously proposed schemes and it has high fidelity. The proposed scheme can be used in unauthorized access prevention method of visual communication or traitor tracking applications which need fast detection process to prevent illegally edited video content from spreading out.Keywords: Editing prevention technique, gradient method, high-quality video, luminance change, visual communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19172507 A Deterministic Polynomial-time Algorithm for the Clique Problem and the Equality of P and NP Complexity Classes
Authors: Zohreh O. Akbari
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In this paper a deterministic polynomial-time algorithm is presented for the Clique problem. The case is considered as the problem of omitting the minimum number of vertices from the input graph so that none of the zeroes on the graph-s adjacency matrix (except the main diagonal entries) would remain on the adjacency matrix of the resulting subgraph. The existence of a deterministic polynomial-time algorithm for the Clique problem, as an NP-complete problem will prove the equality of P and NP complexity classes.Keywords: Clique problem, Deterministic Polynomial-time Algorithm, Equality of P and NP Complexity Classes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17952506 Semi-Automatic Artifact Rejection Procedure Based on Kurtosis, Renyi's Entropy and Independent Component Scalp Maps
Authors: Antonino Greco, Nadia Mammone, Francesco Carlo Morabito, Mario Versaci
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Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.
Keywords: Artifact, EEG, Renyi's entropy, kurtosis, independent component analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18442505 Efficiency of Different GLR Test-statistics for Spatial Signal Detection
Authors: Olesya Bolkhovskaya, Alexander Maltsev
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In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.
Keywords: GLR test-statistic, detection task, generalized likelihood ratio, antenna array, detection curves, performance characteristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15102504 Allocation of Mobile Units in an Urban Emergency Service System
Authors: Dimitra Alexiou
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In an urban area the location allocation of emergency services mobile units, such as ambulances, police patrol cars must be designed so as to achieve a prompt response to demand locations. In this paper the partition of a given urban network into distinct sub-networks is performed such that the vertices in each component are close and simultaneously the sums of the corresponding population in the sub-networks are almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.
Keywords: Distances, Emergency Service, Graph Partition, location.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19282503 Extending the Quantum Entropy to Multidimensional Signal Processing
Authors: Youssef Khmou, Said Safi, Miloud Frikel
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This paper treats different aspects of entropy measure in classical information theory and statistical quantum mechanics, it presents the possibility of extending the definition of Von Neumann entropy to image and array processing. In the first part, we generalize the quantum entropy using singular values of arbitrary rectangular matrices to measure the randomness and the quality of denoising operation, this new definition of entropy can be implemented to compare the performance analysis of filtering methods. In the second part, we apply the concept of pure state in quantum formalism to generalize the maximum entropy method for narrowband and farfield source localization problem. Several computer simulation results are illustrated to demonstrate the effectiveness of the proposed techniques.Keywords: Von Neumann entropy, Filtering, array, DoA, Maximum Entropy Method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24942502 Performance Analysis of Digital Signal Processors Using SMV Benchmark
Authors: Erh-Wen Hu, Cyril S. Ku, Andrew T. Russo, Bogong Su, Jian Wang
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Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.Keywords: digital signal processors, DSP benchmark, instruction level parallelism, modified cyclomatic complexity, performance analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15962501 Noise Removal from Surface Respiratory EMG Signal
Authors: Slim Yacoub, Kosai Raoof
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The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43132500 Motion Detection Method for Clutter Rejection in the Bio-Radar Signal Processing
Authors: Carolina Gouveia, José Vieira, Pedro Pinho
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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.Keywords: Bio-signals, DC Component, Doppler Effect, ellipse fitting, radar, SDR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7802499 Evaluating the Innovation Ability of Manufacturing Resources
Authors: M.F. Zaeh, G. Reinhart, U. Lindemann, F. Karl, W. Biedermann
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Due to today-s turbulent environment, manufacturing resources, particularly in assembly, must be reconfigured frequently. These reconfigurations are caused by various, partly cyclic, influencing factors. Hence, it is important to evaluate the innovation ability - the capability of resources to implement innovations quickly and efficiently without large expense - of manufacturing resources. For this purpose, a new methodology is presented in this article. Within the methodology, design structure matrices and graph theory are used. The results of the methodology include different indices to evaluate the innovation ability of the manufacturing resources. Due to the cyclicity of the influencing factors, the methodology can be used to synchronize the realization of adaptations.
Keywords: Changeability, Cycle Management, Design StructureMatrices, Graph Theory, Manufacturing Resource Planning, Production Management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14742498 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants
Authors: S. Safi, A. Zeroual
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In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14402497 Analysis of EEG Signals Using Wavelet Entropy and Approximate Entropy: A Case Study on Depression Patients
Authors: Subha D. Puthankattil, Paul K. Joseph
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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.
Keywords: EEG, Depression, Wavelet entropy, Approximate entropy, Relative Wavelet energy, Multiresolution decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36262496 Parameters Extraction for Pseudomorphic HEMTs Using Genetic Algorithms
Authors: Mazhar B. Tayel, Amr H. Yassin
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A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.
Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22552495 An Approach to Noise Variance Estimation in Very Low Signal-to-Noise Ratio Stochastic Signals
Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić
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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.
Keywords: Noise, signal-to-noise ratio, stochastic signals, variance estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22462494 A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model
Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You
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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.Keywords: Clustering algorithm, potential function, speech signal, the UBSS model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 663