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Performance improvement of deep learning architectures for phonocardiogram signal classification using fast fourier transform 9

Performance improvement of deep learning architectures for p...

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9th International Conference on Advances in Computing and Communication, ICACC 2019

作者： Gopika, P. Sowmya, V. Gopalakrishnan, E.A. Soman, K.P. Amrita Vishwa Vidyapeetham Center for Computational Engineering and Networking Coimbatore India

ISBN: (纸本)9781728155234

Phonocardiogram known as PCG plays a significant role in the early diagnosis of cardiac abnormalities. Phonocardiogram can be used as initial diagnostics tool in remote applications due to its simplicity and cost effectiveness. Instead of disease specific approach, the proposed work aims for the single architecture that could diagnose different cardiac abnormality from the PCG signals collected from various sources. Our study also shows the effectiveness of using Fast Fourier Transform (FFT) in signal processing applications. It avoids the trivial preprocessing and feature extraction mechanisms with the promising results. © 2019 IEEE.

关键词： Fast Fourier transforms

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Deep Learning Framework for Fingerspelling System using CNN

Deep Learning Framework for Fingerspelling System using CNN

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International Conference on Communications and Signal Processing

作者： Chakravartula Raghavachari GA Shanmugha Sundaram Center for Computational Engineering and Networking Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India SIERS Research Laboratory and also with both the Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham India

ISBN: (数字)9781728149882

ISBN: (纸本)9781728149899

Sign language is used for communication among the hearing-challenged-cum-speech-challenged community. It is the language that uses facial expressions, movements of hands and other body parts. Indian Sign language (ISL) is commonly used sign language, in India. These days, online interpreters are available for translating the sign language to common language and vice versa. But it requires an expert who can translate in both ways and also they charge. Thus, the communication between the hearing-challenged-cum-speech-challenged community and the rest has become difficult and costly. This causes isolation of the hearing-challenged-cum-speech-challenged community from the rest of society. Hence, this work focuses on bridging the communication gap between the two. One important aspect of sign language is finger spelling. Through finger spelling, a word that lacks a particular sign in sign language can be expressed by spelling each alphabet of that word. Here, a vision based finger spelling system using Convolutional Neural Networks (CNN) is created. The proposed CNN model performs as par with the InceptionV3 and better than ResNet and VGG16 models.

关键词： Assistive technology Machine learning Gesture recognition Convolution Training Kernel Standards

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Phase-modulated stepped frequency waveform design for low probability of detection radar signals 4th

Phase-modulated stepped frequency waveform design for low pr...

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4th International Symposium on Intelligent Systems Technologies and Applications, ISTA 2018

作者： Vignesh, R. Sundaram, G. A. Shanmugha Gandhiraj, R. Amrita School of Engineering Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore India Department of Electronics and Communications Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India SIERS Research Laboratory ASE Coimbatore Amrita University Coimbatore India

ISBN: (纸本)9789811360947

Recent developments in radar electronic warfare in the modern battlefield have led to advancement in various signal processing technologies that have increased the potential to detect and jam the radar signals. Signal detection and jamming results in various problems such as false target detection, false alarm rate, and so on. The introduction of modern electronic support measure (ESM) and radar warning receiver (RWR) provides various threats to the radar operations. To hide and to survive the enemy attack, the radars should have low probability of interception (LPI) or low probability of detection (LPD). In order to improve the robustness of radar signals, in a manner that evades detection, interception, and cognition, complex waveforms which are less susceptible to jammers and intercept receivers, a new technique is presented in the work reported here. Radars are used in target tracking systems to estimate the range and velocity of both stationary and moving objects. Phase-modulated signals help in determining the velocity of the target using Doppler information. Here, a new approach to the pulse compression techniques by means of phase modulating the stepped frequency waveform (SFW) with constant and varying step sizes is advanced. In order to make the signal less detectable, phase modulation techniques such as Barker codes and polyphase codes have been employed in tandem. A random choice of varying frequency step size compresses the ambiguity function estimates of target range, improves covert detection, and reduces the interferences caused by various sources. The comparison between SFW with either a constant or a varying frequency step size is performed. The generated waveforms have wide bandwidth and less peak power which are considered to be integral attributes of LPI signals. Also, the waveform properties based on different radar parameters are studied and analyzed using the ambiguity functions plots. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Probability

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Effect of waveform coding on stepped frequency modulated pulsed radar transmit signals 4th

Effect of waveform coding on stepped frequency modulated pul...

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4th International Symposium on Intelligent Systems Technologies and Applications, ISTA 2018

作者： Priyanga, G. Shanmugha Sundaram, G.A. Amrita School of Engineering Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore India Department of Electronics and Communications Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India SIERS Research Laboratory ASE Coimbatore Amrita University Coimbatore India

ISBN: (纸本)9789811360947

The choice of a waveform in a radar system plays a predominant role in characterizing the radars’ ability to differentiate two closely spaced targets in both range and Doppler domains. RADAR waveforms are broadly categorized into two types, viz. pulsed or continuous waveform. A waveform can be analyzed in both time and frequency domains. The frequency domain analysis informs about the range and Doppler resolution of the radar target. The ambiguity of the transmitted waveform in both range and Doppler domain is used to understand the critical parameters used in the design and performance of any radar system. Precise radar measurements like range and Doppler calculation need higher resolution in both domains. But, in a pulsed radar system, there is an important factor of trade-off between range resolution and sensitivity, that necessitates pulses of smaller width, while the pulse energy in the transmitted waveform requires a longer pulse duration. An approach to overcome this trade-off is pulse compression which modulates the pulses to be transmitted. In the work reported here, a new approach to pulse compression technique is provided by modulating the transmitted waveform of a stepped frequency waveform (SFW) with orthogonal frequency-division multiplexing (OFDM). The reported work evaluates the performance of frequency spacings that are either uniform or non-uniform in the SFW waveform in terms of their maximum detection capability, observed from the graphs of delay and Doppler cuts in the ambiguity function plot. Various phase coding techniques are also used to define the non-uniform spaced SFW. The robustness of radar waveforms in terms of their static and dynamic resolution parameters, as well as their ambiguities, is also evaluated. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Orthogonal frequency division multiplexing

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Impact analysis of LFM jammer signals on stepped frequency PAM4 RADAR waveforms 4th

Impact analysis of LFM jammer signals on stepped frequency P...

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4th International Symposium on Intelligent Systems Technologies and Applications, ISTA 2018

作者： Keerthana, K. Shanmugha Sundaram, G.A. Center for Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Department of Electronics and Communications Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India SIERS Research Laboratory ASE Coimbatore Amrita University Coimbatore India

ISBN: (纸本)9789811360947

Recognizing targets becomes a difficult process when the jamming signal tries to overwhelm the signals detected at a radar receiver. In radar systems, the most common type of signals used are the continuous and pulsed waveforms. For enhanced target detection and range resolution, continuous changes in the waveforms are required in pulsed waveforms. For continuous waveforms, such changes are not required, and both transmitter and receiver are working as two separate antenna systems as in a monostatic radar, which can provide a high signal-to-noise ratio (SNR). In this work, the linear frequency modulated (LFM) waveform is introduced as a strong jamming signal. The radar signals of the compound pulsed radar modulation type are considered here, with the combination of stepped frequency waveform (SFW) and a four-level pulse amplitude modulation (PAM4). The SFW is capable of high range resolution (HRR), while PAM4 can provide a lower bandwidth. This new approach shows characteristics such as better target detection, good range resolution, and proper range measurements, even with the presence of the LFM jamming signal. Simulation is done using a monostatic radar system to analyze the radar operations and performance. Results are investigated in terms of different radar parameters like range-Doppler response, FFT spectrum, target returns, burn-through range, cross-over range, and signal-to-jammer-noise ratio. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Pulse amplitude modulation

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Detection of Interference in C-Band Signals using K-Means Clustering 9

Detection of Interference in C-Band Signals using K-Means Cl...

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9th IEEE International Conference on Communication and Signal Processing, ICCSP 2020

作者： Surya Natarajan, S. Ateesh Varun, R. Shivasubramanian, G. Thamayandran, D. Dharani, M. Gandhiraj, R. Shanmugha Sundaram, G.A. Pradeep Kumar, A.K. Binoy, N.B. Thiruvengadathan, R. Harish Ram, D.S. Amrita School of Engineering Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Coimbatore India SIERS Research Laboratory Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Center for Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781728149882

Interference is a main disruptive phenomenon which degrades the performance of communication systems and in general the quality of signal acquisition. Real-time communication through a channel is never free from signal disrupting phenomena like interference, distortion and noise. Hence it is essential to study their effects and methods of identifying them. Conventional methods to identify, estimate and mitigate interference are model driven. A data driven approach is far more efficient and adaptable than model driven methods. In this paper, we exemplify the use of a data driven approach to identify signatures of interference based on analysis of the acquired RF data. © 2020 IEEE.

关键词： K-means clustering

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Evidence of Scatter in C-band Spatio-temporal Signals using Machine Learning Models 9

Evidence of Scatter in C-band Spatio-temporal Signals using ...

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9th IEEE International Conference on Communication and Signal Processing, ICCSP 2020

作者： Harun Surej, I. Karthic, S. Vigneshwara, G. Jeyashri, T. Thiruvengadathan, R. Gandhiraj, R. Pradeep Kumar, K.A. Binoy, B.N. Shanmugha Sundaram, G.A. Harish Ram, D.S. Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Amrita Vishwa Vidyapeetham Center for Computational Engineering and Networking Amrita School of Engineering Coimbatore India SIERS Research Laboratory Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781728149882

Signal propagating through free space in wireless communication is subject to additive noise by line-of-sight and non-line-of-sight objects in the propagation medium. This leads to a lot of interference and scattering due to multipath effects. This research work aims to identify such contributors in the propagation channel and characterize them based on their signal scattering property. A data-driven modelling approach is used in place of the traditional math-based modelling. K-means clustering along with other data interpretation methods were used to identify the scatterers. The scatterers are either characterized as absorbing or reflecting type based on the way the signal is affected. Five independent datasets using the C-band frequency were collected under laboratory conditions and used for the study. The ideal dataset from the manufacturer was used as the benchmark. The results identified the scatterers from the experimental dataset and enabled the estimation of their dimensions and material composition in laboratory conditions. © 2020 IEEE.

关键词： K-means clustering

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Identifying epiphytes in drones photos with a conditional generative adversarial network (C-GAN)

Identifying epiphytes in drones photos with a conditional ge...

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American Society for Photogrammetry and Remote Sensing, ASPRS 2020 Annual Conference

作者： Shashank, A. Sajithvariyar, V.V. Sowmya, V. Soman, K.P. Sivanpillai, R. Brown, G.K. Center for Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham CoimbatoreTN641 112 India Wyoming GIS Center University of Wyoming LaramieWY82072 United States Department of Botany University of Wyoming LaramieWY82072 United States

Unmanned Aerial Vehicle (UAV) missions often collect large volumes of imagery data. However, not all images will have useful information, or be of sufficient quality. Manually sorting these images and selecting useful data are both time consuming and prone to interpreter bias. Deep neural network algorithms are capable of processing large image datasets and can be trained to identify specific targets. Generative Adversarial Networks (GANs) consist of two competing networks, Generator and Discriminator that can analyze, capture, and copy the variations within a given dataset. In this study, we selected a variant of GAN called Conditional-GAN that incorporates an additional label parameter, for identifying epiphytes in photos acquired by a UAV in forests within Costa Rica. We trained the network with 70%, 80%, and 90% of 119 photos containing the target epiphyte, Werauhia kupperiana (Bromeliaceae) and validated the algorithm's performance using a validation data that were not used for training. The accuracy of the output was measured using structural similarity index measure (SSIM) index and histogram correlation (HC) coefficient. Results obtained in this study indicated that the output images generated by C-GAN were similar (average SSIM = 0.89 - 0.91 and average HC 0.97 - 0.99) to the analyst annotated images. However, C-GAN had difficulty to identify when the target plant was away from the camera, was not well lit, or covered by other plants. Results obtained in this study demonstrate the potential of C-GAN to reduce the time spent by botanists to identity epiphytes in images acquired by UAVs. © 2020 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Generative adversarial networks

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Refined Zero Band Filtering for Estimation of Instants of Significant Excitation from Emotive Speech

Refined Zero Band Filtering for Estimation of Instants of Si...

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IEEE India Conference (INDICON)

作者： R. Ashwini D. Govind Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham (University) Amritanagar Coimbatore Tamilnadu India Koneru Lakshmaiah Education Foundation (KLEF) Greenfields Vaddeswaram Guntur Andhra Pradesh India

ISBN: (纸本)9781665441766

The objective of the present work is to improve the estimation of instants of significant excitation from speech signals with emotions. In particular, the work focusses on the refinement to the zero band filtering (ZBF) based instants estimation for emotive speech and singing voices. The choice of speech data with emotions is due to the nature of the data with rapid variations in the prosodic parameters which in turn poses challenges in the accurate estimation of instants. The ZBF approach, being the reliable method for instants estimation from the speech data with rapid prosodic variations, suffers from degraded performance due to the occurrence of spurious zero crossings in zero band filtered signal (ZBFS). The refinement is introduced by suppressing the spurious zero crossings by the low pass filtering of conventional ZBF segments with cutoff frequencies which are adaptively estimated as average pitch values obtained from each of the segments. The effectiveness of the refined ZBF method is confirmed by relative drop in the false estimation rates and miss rates of the hypothesized instants of significant excitation for emotive speech.

关键词： Filtering Conferences Cutoff frequency Estimation Reliability

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Effectiveness of Wavelet Synchrosqueezed Transform for Improved Epoch Estimation from Telephonic Speech Signals Using Zero Frequency Filtering

Effectiveness of Wavelet Synchrosqueezed Transform for Impro...

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IEEE India Conference (INDICON)

作者： M. Chandni D. Govind Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham (University) AmritanagarCoimbatore Tamilnadu India Koneru Lakshmaiah Education Foundation (KLEF) Greenfields Vaddeswaram Guntur Andhra Pradesh India

ISBN: (纸本)9781665441766

Epochs are impulse like discontinuities in speech that represent the instants of glottal closure during phonation. The accurate estimation of epochs is essential for epoch synchronous speech processing. There are many algorithms proposed in the literature for the accurate estimation of epochs from speech signals. However majority of those algorithms show degradation during the epoch extraction from telephonic speech signals. The restricted bandwidth (300 Hz-3.4 kHz) of the telephone channel is the reason for degradation in epoch estimation performance. Therefore, the objective of the present work is to propose a wavelet synchrosqueezed transform (WSST) based signal preprocessing stage to improve the performance of zero frequency filtering (ZFF) which is a well known epoch estimation method. Improved time-frequency resolution of WSST reinforce the strength of impulses around the fundamental components to estimate accurate epoch locations. A multiscale product of WSST modified speech and the original speech is computed further enhance the impulse like discontinuities. Effectiveness of the proposed method is confirmed by the epoch estimation performance analysis of phonetically balanced CMU-Arctic database with electroglottogram recordings. The telephone quality in the database is simulated using G.191 software tools.

关键词： Wavelet transforms Degradation Time-frequency analysis Filtering Databases Estimation Speech enhancement

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