Search results for: fluctuation of biological signal
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4002

Search results for: fluctuation of biological signal

3972 Comparative Analysis of Two Approaches to Joint Signal Detection, ToA and AoA Estimation in Multi-Element Antenna Arrays

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

Abstract:

In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: antenna array, signal detection, ToA, AoA estimation

Procedia PDF Downloads 463
3971 Numerical Investigations of Unstable Pressure Fluctuations Behavior in a Side Channel Pump

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

Abstract:

The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 101
3970 Musical Tesla Coil Controlled by an Audio Signal Processed in Matlab

Authors: Sandra Cuenca, Danilo Santana, Anderson Reyes

Abstract:

The following project is based on the manipulation of audio signals through the Matlab software, which has an audio signal that is modified, and its resultant obtained through the auxiliary port of the computer is passed through a signal amplifier whose amplified signal is connected to a tesla coil which has a behavior like a vumeter, the flashes at the output of the tesla coil increase and decrease its intensity depending on the audio signal in the computer and also the voltage source from which it is sent. The amplified signal then passes to the tesla coil being shown in the plasma sphere with the respective flashes; this activation is given through the specified parameters that we want to give in the MATLAB algorithm that contains the digital filters for the manipulation of our audio signal sent to the tesla coil to be displayed in a plasma sphere with flashes of the combination of colors commonly pink and purple that varies according to the tone of the song.

Keywords: auxiliary port, tesla coil, vumeter, plasma sphere

Procedia PDF Downloads 51
3969 Effects of Charge Fluctuating Positive Dust on Linear Dust-Acoustic Waves

Authors: Sanjit Kumar Paul, A. A. Mamun, M. R. Amin

Abstract:

The Linear propagation of the dust-acoustic wave in a dusty plasma consisting of Boltzmann distributed electrons and ions and mobile charge fluctuating positive dust grains has been investigated by employing the reductive perturbation method. It has been shown that the dust charge fluctuation is a source of dissipation and its responsible for the formation of the dust-acoustic waves in such a dusty plasma. The basic features of such dust-acoustic waves have been identified. It has been proposed to design a new laboratory experiment which will be able to identify the basic features of the dust-acoustic waves predicted in this theoretical investigation.

Keywords: dust acoustic waves, dusty plasma, Boltzmann distributed electrons, charge fluctuation

Procedia PDF Downloads 610
3968 Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment

Authors: Monica Sharma, Harjit Pal Singh, Jasbinder Singh, Manju Bala

Abstract:

In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal.

Keywords: VoIP, interleaving, packet loss, packet size, background noise

Procedia PDF Downloads 451
3967 Development of a Tesla Music Coil from Signal Processing

Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

Abstract:

This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

Procedia PDF Downloads 78
3966 Multiple Relaxation Times in the Gibbs Ensemble Monte Carlo Simulation of Phase Separation

Authors: Bina Kumari, Subir K. Sarkar, Pradipta Bandyopadhyay

Abstract:

The autocorrelation function of the density fluctuation is studied in each of the two phases in a Gibbs Ensemble Monte Carlo (GEMC) simulation of the problem of phase separation for a square well potential with various values of its range. We find that the normalized autocorrelation function is described very well as a linear combination of an exponential function with a time scale τ₂ and a stretched exponential function with a time scale τ₁ and an exponent α. Dependence of (α, τ₁, τ₂) on the parameters of the GEMC algorithm and the range of the square well potential is investigated and interpreted. We also analyse the issue of how to choose the parameters of the GEMC simulation optimally.

Keywords: autocorrelation function, density fluctuation, GEMC, simulation

Procedia PDF Downloads 156
3965 Renewable Integration Algorithm to Compensate Photovoltaic Power Using Battery Energy Storage System

Authors: Hyung Joo Lee, Jin Young Choi, Gun Soo Park, Kyo Sun Oh, Dong Jun Won

Abstract:

The fluctuation of the output of the renewable generator caused by weather conditions must be mitigated because it imposes strain on the system and adversely affects power quality. In this paper, we focus on mitigating the output fluctuation of the photovoltaic (PV) using battery energy storage system (BESS). To satisfy tight conditions of system, proposed algorithm is developed. This algorithm focuses on adjusting the integrated output curve considering state of capacity (SOC) of the battery. In this paper, the simulation model is PSCAD / EMTDC software. SOC of the battery and the overall output curve are shown using the simulation results. We also considered losses and battery efficiency.

Keywords: photovoltaic generation, battery energy storage system, renewable integration, power smoothing

Procedia PDF Downloads 253
3964 Optimal Geothermal Borehole Design Guided By Dynamic Modeling

Authors: Hongshan Guo

Abstract:

Ground-source heat pumps provide stable and reliable heating and cooling when designed properly. The confounding effect of the borehole depth for a GSHP system, however, is rarely taken into account for any optimization: the determination of the borehole depth usually comes prior to the selection of corresponding system components and thereafter any optimization of the GSHP system. The depth of the borehole is important to any GSHP system because the shallower the borehole, the larger the fluctuation of temperature of the near-borehole soil temperature. This could lead to fluctuations of the coefficient of performance (COP) for the GSHP system in the long term when the heating/cooling demand is large. Yet the deeper the boreholes are drilled, the more the drilling cost and the operational expenses for the circulation. A controller that reads different building load profiles, optimizing for the smallest costs and temperature fluctuation at the borehole wall, eventually providing borehole depth as the output is developed. Due to the nature of the nonlinear dynamic nature of the GSHP system, it was found that between conventional optimal controller problem and model predictive control problem, the latter was found to be more feasible due to a possible history of both the trajectory during the iteration as well as the final output could be computed and compared against. Aside from a few scenarios of different weighting factors, the resulting system costs were verified with literature and reports and were found to be relatively accurate, while the temperature fluctuation at the borehole wall was also found to be within acceptable range. It was therefore determined that the MPC is adequate to optimize for the investment as well as the system performance for various outputs.

Keywords: geothermal borehole, MPC, dynamic modeling, simulation

Procedia PDF Downloads 266
3963 Forensic Analysis of Signal Messenger on Android

Authors: Ward Bakker, Shadi Alhakimi

Abstract:

The amount of people moving towards more privacy focused instant messaging applications has grown significantly. Signal is one of these instant messaging applications, which makes Signal interesting for digital investigators. In this research, we evaluate the artifacts that are generated by the Signal messenger for Android. This evaluation was done by using the features that Signal provides to create artifacts, whereafter, we made an image of the internal storage and the process memory. This image was analysed manually. The manual analysis revealed the content that Signal stores in different locations during its operation. From our research, we were able to identify the artifacts and interpret how they were used. We also examined the source code of Signal. Using our obtain knowledge from the source code, we developed a tool that decrypts some of the artifacts using the key stored in the Android Keystore. In general, we found that most artifacts are encrypted and encoded, even after decrypting some of the artifacts. During data visualization, some artifacts were found, such as that Signal does not use relationships between the data. In this research, two interesting groups of artifacts were identified, those related to the database and those stored in the process memory dump. In the database, we found plaintext private- and group chats, and in the memory dump, we were able to retrieve the plaintext access code to the application. Nevertheless, we conclude that Signal contains a wealth of artifacts that could be very valuable to a digital forensic investigation.

Keywords: forensic, signal, Android, digital

Procedia PDF Downloads 49
3962 Neural Network Based Path Loss Prediction for Global System for Mobile Communication in an Urban Environment

Authors: Danladi Ali

Abstract:

In this paper, we measured GSM signal strength in the Dnepropetrovsk city in order to predict path loss in study area using nonlinear autoregressive neural network prediction and we also, used neural network clustering to determine average GSM signal strength receive at the study area. The nonlinear auto-regressive neural network predicted that the GSM signal is attenuated with the mean square error (MSE) of 2.6748dB, this attenuation value is used to modify the COST 231 Hata and the Okumura-Hata models. The neural network clustering revealed that -75dB to -95dB is received more frequently. This means that the signal strength received at the study is mostly weak signal

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment and model

Procedia PDF Downloads 353
3961 Comparison of Formation Sensitivity Gap between Islamic Maybank Indonesia and Islamic Maybank Malaysia

Authors: Puji Sucia Sukmaningrum, Achsania Hendratmi, Noven Suprayogi, Muhammad Madyan

Abstract:

Theoretically, Islamic banks in Indonesia and Malaysia not necessarily aware to the interest rate fluctuation, since they don’t use interest-based instruments. Both countries use dual banking system in which Islamic and conventional banking system are exist. This situation makes the profit-sharing level of the Islamic banks will be indirectly affected by the interest rate fluctuation from the conventional banks system. One of the risk management tools for anticipating the risk of interest rate fluctuation is gap management, which has purpose to narrow the difference between Rate Sensitive Asset (RSA) and Rate Sensitive Liability (RSL). This formed gap will give the information about the risk potential in Islamic banks which respect to the fluctuation on the interest rate. This study aims to determine the position of the gap formed at Islamic Maybank Indonesia and Islamic Maybank Malaysia, and analyze the difference in the formation of gap based on the period of sensitivity. This study is a quantitative research with comparative study using sensitivity gap analysis, independent sample t-test, and Mann-Whitney method. The data being used was secondary data from Maturity Profile contained in the Annual Financial Report of Islamic Maybank Indonesia and Islamic Maybank Malaysia from 2011 to 2015 period. The result shows that, cumulatively the formation of the gap was negative gap. From the results of independent sample t-test and Mann-Whitney, the formation of the gap in Islamic Maybank Indonesia and Islamic Maybank Malaysia for a period of sensitivity of ≤ 1 month and >1-3 months show a significant difference, while the period of sensitivity >3-12 months does not. The result shows, even though Indonesia and Malaysia using same dual banking systems, the gap values are different. The difference in debt policy between Indonesia and Malaysia also affecting the gap sensitivity in debt. In can be concluded that each country needs an appropriate gap management to support its Islamic banking performance specifically.

Keywords: assets and liability management, gap management, interest rate risk, Islamic bank

Procedia PDF Downloads 240
3960 Heart Murmurs and Heart Sounds Extraction Using an Algorithm Process Separation

Authors: Fatima Mokeddem

Abstract:

The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

Procedia PDF Downloads 112
3959 Sparsity Order Selection and Denoising in Compressed Sensing Framework

Authors: Mahdi Shamsi, Tohid Yousefi Rezaii, Siavash Eftekharifar

Abstract:

Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising.

Keywords: compressed sensing, data denoising, model order selection, sparse representation

Procedia PDF Downloads 455
3958 Theoretical BER Analyzing of MPSK Signals Based on the Signal Space

Authors: Jing Qing-feng, Liu Danmei

Abstract:

Based on the optimum detection, signal projection and Maximum A Posteriori (MAP) rule, Proakis has deduced the theoretical BER equation of Gray coded MPSK signals. Proakis analyzed the BER theoretical equations mainly based on the projection of signals, which is difficult to be understood. This article solve the same problem based on the signal space, which explains the vectors relations among the sending signals, received signals and noises. The more explicit and easy-deduced process is illustrated in this article based on the signal space, which can illustrated the relations among the signals and noises clearly. This kind of deduction has a univocal geometry meaning. It can explain the correlation between the production and calculation of BER in vector level.

Keywords: MPSK, MAP, signal space, BER

Procedia PDF Downloads 318
3957 Optimization of Three Phase Squirrel Cage Induction Motor

Authors: Tunahan Sapmaz, Harun Etçi, İbrahim Şenol, Yasemin Öner

Abstract:

Rotor bar dimensions have a great influence on the air-gap magnetic flux density. Therefore, poor selection of this parameter during the machine design phase causes the air-gap magnetic flux density to be distorted. Thus, it causes noise, torque fluctuation, and losses in the induction motor. On the other hand, the change in rotor bar dimensions will change the resistance of the conductor, so the current will be affected. Therefore, the increase and decrease of rotor bar current affect operation, starting torque, and efficiency. The aim of this study is to examine the effect of rotor bar dimensions on the electromagnetic performance criteria of the induction motor. Modeling of the induction motor is done by the finite element method (FEM), which is a very powerful tool. In FEM, the results generally focus on performance criteria such as torque, torque fluctuation, efficiency, and current.

Keywords: induction motor, finite element method, optimization, rotor bar

Procedia PDF Downloads 95
3956 Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification

Authors: Zin Mar Lwin

Abstract:

Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

Procedia PDF Downloads 248
3955 Exact Formulas of the End-To-End Green’s Functions in Non-hermitian Systems

Authors: Haoshu Li, Shaolong Wan

Abstract:

The recent focus has been on directional signal amplification of a signal input at one end of a one-dimensional chain and measured at the other end. The amplification rate is given by the end-to-end Green’s functions of the system. In this work, we derive the exact formulas for the end-to-end Green's functions of non-Hermitian single-band systems. While in the bulk region, it is found that the Green's functions are displaced from the prior established integral formula by O(e⁻ᵇᴸ). The results confirm the correspondence between the signal amplification and the non-Hermitian skin effect.

Keywords: non-Hermitian, Green's function, non-Hermitian skin effect, signal amplification

Procedia PDF Downloads 112
3954 Speech Enhancement Using Kalman Filter in Communication

Authors: Eng. Alaa K. Satti Salih

Abstract:

Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.

Keywords: autoregressive process, Kalman filter, Matlab, noise speech

Procedia PDF Downloads 315
3953 Subband Coding and Glottal Closure Instant (GCI) Using SEDREAMS Algorithm

Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

Abstract:

In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

Procedia PDF Downloads 326
3952 Analysis of Injection-Lock in Oscillators versus Phase Variation of Injected Signal

Authors: M. Yousefi, N. Nasirzadeh

Abstract:

In this paper, behavior of an oscillator under injection of another signal has been investigated. Also, variation of output signal amplitude versus injected signal phase variation, the effect of varying the amplitude of injected signal and quality factor of the oscillator has been investigated. The results show that the locking time depends on phase and the best locking time happens at 180-degrees phase. Also, the effect of injected lock has been discussed. Simulations show that the locking time decreases with signal injection to bulk. Locking time has been investigated versus various phase differences. The effect of phase and amplitude changes on locking time of a typical LC oscillator in 180 nm technology has been investigated.

Keywords: analysis, oscillator, injection-lock oscillator, phase modulation

Procedia PDF Downloads 322
3951 Impact of Climate Change on Water Level and Properties of Gorgan Bay in the Southern Caspian Sea

Authors: Siamak Jamshidi

Abstract:

The Caspian Sea is the Earth's largest inland body of water. One of the most important issues related to the sea is water level changes. For measuring and recording Caspian Sea water level, there are at least three gauges and radar equipment in Anzali, Nowshahr and Amirabad Ports along the southern boundary of the Caspian Sea. It seems that evaporation, hotter surface air temperature, and in general climate change is the main reasons for its water level fluctuations. Gorgan Bay in the eastern part of the southern boundary of the Caspian Sea is one of the areas under the effect of water level fluctuation. Based on the results of field measurements near the Gorgan Bay mouth temperature ranged between 24°C–28°C and salinity was about 13.5 PSU in midsummer while temperature changed between 10-11.5°C and salinity mostly was 15-16.5 PSU in mid-winter. The decrease of Caspian Sea water level and rivers outflow are the two most important factors for the increase in water salinity of the Gorgan Bay. Results of field observations showed that, due to atmospheric factors, climate changes and decreasing of precipitation over the southern basin of the Caspian Sea during last decades, the water level of bay was reduced around 0.5 m.

Keywords: Caspian Sea, Gorgan Bay, water level fluctuation, climate changes

Procedia PDF Downloads 141
3950 ICanny: CNN Modulation Recognition Algorithm

Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

Abstract:

Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

Procedia PDF Downloads 162
3949 Cyclostationary Analysis of Polytime Coded Signals for LPI Radars

Authors: Metuku Shyamsunder, Kakarla Subbarao, P. Prasanna

Abstract:

In radars, an electromagnetic waveform is sent, and an echo of the same signal is received by the receiver. From this received signal, by extracting various parameters such as round trip delay, Doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper, a brief discussion on LPI radar and its modulation (polytime code (PT1)), detection (cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.

Keywords: LPI radar, polytime codes, cyclostationary DFSM, FAM

Procedia PDF Downloads 444
3948 Sparse Signal Restoration Algorithm Based on Piecewise Adaptive Backtracking Orthogonal Least Squares

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

Procedia PDF Downloads 112
3947 FPGA Implementation of a Marginalized Particle Filter for Delineation of P and T Waves of ECG Signal

Authors: Jugal Bhandari, K. Hari Priya

Abstract:

The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

Procedia PDF Downloads 341
3946 Numerical Experiments for the Purpose of Studying Space-Time Evolution of Various Forms of Pulse Signals in the Collisional Cold Plasma

Authors: N. Kh. Gomidze, I. N. Jabnidze, K. A. Makharadze

Abstract:

The influence of inhomogeneities of plasma and statistical characteristics on the propagation of signal is very actual in wireless communication systems. While propagating in the media, the deformation and evaluation of the signal in time and space take place and on the receiver we get a deformed signal. The present article is dedicated to studying the space-time evolution of rectangular, sinusoidal, exponential and bi-exponential impulses via numerical experiment in the collisional, cold plasma. The presented method is not based on the Fourier-presentation of the signal. Analytically, we have received the general image depicting the space-time evolution of the radio impulse amplitude that gives an opportunity to analyze the concrete results in the case of primary impulse.

Keywords: collisional, cold plasma, rectangular pulse signal, impulse envelope

Procedia PDF Downloads 348
3945 Recent Advancement in Fetal Electrocardiogram Extraction

Authors: Savita, Anurag Sharma, Harsukhpreet Singh

Abstract:

Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

Procedia PDF Downloads 378
3944 Microstructure and Excess Conductivity of Bulk, Ag-Added FeSe Superconductors

Authors: Michael Koblischka, Yassine Slimani, Thomas Karwoth, Anjela Koblischka-Veneva, Essia Hannachi

Abstract:

On bulk FeSe superconductors containing different additions of Ag, a thorough investigation of the microstructures was performed using optical microscopy, SEM and TEM. The electrical resistivity was measured using four-point measurements in the temperature range 2 K ≤ T ≤ 150 K. The data obtained are analyzed in the framework of the excess conductivity approach using the Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), onedimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuation regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), the lower and upper critical magnetic fields (Bc1 and Bc2), the critical current density (Jc) and numerous other superconducting parameters were estimated with respect to the Ag content in the samples. The data reveal a reduction of the resistivity and a strong decrease of ξc(0) when doping the 11-samples with silver. The optimum content of the Ag-addition is found at 4 wt.-% Ag, yielding the highest critical current density.

Keywords: iron-based superconductors, FeSe, Ag-addition, excess conductivity, microstructure

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3943 Selecting the Best RBF Neural Network Using PSO Algorithm for ECG Signal Prediction

Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

Abstract:

In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

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