Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646309
Aviel Adler, Ofer Schwartz, S. Gannot
Speech enhancement and source separation are well-known challenges in the context of hands-free communication and automatic speech recognition. The multichannel Wiener filter (MCWF) that satisfies the minimum mean square error (MMSE) criterion, is a fundamental speech enhancement tool. However, it can suffer from speech distortion, especially when the noise level is high. The speech distortion weighted multichannel Wiener filter (SDW-MWF) was therefore proposed to control the tradeoff between noise reduction and speech distortion for the single-speaker case. In this paper, we generalize this estimator and propose a method for controlling this tradeoff in the multi-speaker case. The proposed estimator is decomposed into two successive stages: 1) a multi-speaker linearly constrained minimum variance (LCMV), which is solely determined by the spatial characteristics of the speakers; and 2) a multi-speaker Wiener postfilter (PF), which is responsible for reducing the residual noise. The proposed PF consists of several controlling parameters that can almost independently control the tradeoff between the distortion of each speaker and the total noise reduction.
{"title":"A Weighted Multichannel Wiener Filter and its Decomposition to LCMV Beam Former and Post-Filter for Source Separation and Noise Reduction","authors":"Aviel Adler, Ofer Schwartz, S. Gannot","doi":"10.1109/ICSEE.2018.8646309","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646309","url":null,"abstract":"Speech enhancement and source separation are well-known challenges in the context of hands-free communication and automatic speech recognition. The multichannel Wiener filter (MCWF) that satisfies the minimum mean square error (MMSE) criterion, is a fundamental speech enhancement tool. However, it can suffer from speech distortion, especially when the noise level is high. The speech distortion weighted multichannel Wiener filter (SDW-MWF) was therefore proposed to control the tradeoff between noise reduction and speech distortion for the single-speaker case. In this paper, we generalize this estimator and propose a method for controlling this tradeoff in the multi-speaker case. The proposed estimator is decomposed into two successive stages: 1) a multi-speaker linearly constrained minimum variance (LCMV), which is solely determined by the spatial characteristics of the speakers; and 2) a multi-speaker Wiener postfilter (PF), which is responsible for reducing the residual noise. The proposed PF consists of several controlling parameters that can almost independently control the tradeoff between the distortion of each speaker and the total noise reduction.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130891176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646121
D. Rzepka, D. Koscielnik, Jakub Szyduczynski, M. Pawlak, M. Miśkowicz
The paper is focused on methods of the perfect signal recovery based on the frame theory, and the approximate fast reconstruction with truncated Fourier series for inputs encoded by Sample-and-Hold Asynchronous Sigma Delta Modulation (SH-ASDM). The comparative analysis shows that the signal recovery for the SH-ASDM is characterized by significantly lower computational complexity than for the classical ASDM.
{"title":"Recovery of Signals Encoded by Sample-and-Hold Asynchronous Sigma-Delta Modulation","authors":"D. Rzepka, D. Koscielnik, Jakub Szyduczynski, M. Pawlak, M. Miśkowicz","doi":"10.1109/ICSEE.2018.8646121","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646121","url":null,"abstract":"The paper is focused on methods of the perfect signal recovery based on the frame theory, and the approximate fast reconstruction with truncated Fourier series for inputs encoded by Sample-and-Hold Asynchronous Sigma Delta Modulation (SH-ASDM). The comparative analysis shows that the signal recovery for the SH-ASDM is characterized by significantly lower computational complexity than for the classical ASDM.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131168761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646195
Tzoof Hemed, Nitai Lavie, R. Kaplan
Deep Neural Networks (DNN), contain multiple convolutional and several fully connected layers, require considerable hardware resources to train in a reasonable time. Multiple CPUs, GPUs or FPGAs are usually combined to reduce the training time of a DNN. However, many individuals or small organizations do not possess the resources to obtain multiple hardware units.The contribution of this work is two-fold. First, we present an implementation of a distributed DNN training system that uses multiple small (wimpy) nodes to accelerate the training process. The nodes are mobile smartphone devices, with variable hardware specifications. All DNN training tasks are performed on the small nodes, coordinated by a centralized server. Second, we propose a novel method to mitigate issues arising from the variability in hardware resources. We demonstrate that the method allows training a DNN to high accuracy on known image recognition datasets with multiple small different nodes. The proposed method factors in the contribution from each node according to its run time on a specific training task, relative to the other nodes. In addition, we discuss practical challenges that arise from small node system and suggest several solutions.
{"title":"Distributed Deep Learning on Wimpy Smartphone Nodes","authors":"Tzoof Hemed, Nitai Lavie, R. Kaplan","doi":"10.1109/ICSEE.2018.8646195","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646195","url":null,"abstract":"Deep Neural Networks (DNN), contain multiple convolutional and several fully connected layers, require considerable hardware resources to train in a reasonable time. Multiple CPUs, GPUs or FPGAs are usually combined to reduce the training time of a DNN. However, many individuals or small organizations do not possess the resources to obtain multiple hardware units.The contribution of this work is two-fold. First, we present an implementation of a distributed DNN training system that uses multiple small (wimpy) nodes to accelerate the training process. The nodes are mobile smartphone devices, with variable hardware specifications. All DNN training tasks are performed on the small nodes, coordinated by a centralized server. Second, we propose a novel method to mitigate issues arising from the variability in hardware resources. We demonstrate that the method allows training a DNN to high accuracy on known image recognition datasets with multiple small different nodes. The proposed method factors in the contribution from each node according to its run time on a specific training task, relative to the other nodes. In addition, we discuss practical challenges that arise from small node system and suggest several solutions.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"409 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124345562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646132
D. Rajesh, Ziv Glasser, Y. Gorodetski, S. Sternklar, D. Cheskis
The rapid growing interest in the field of plasmonics comes from advance nanotechnologies involving nanophotonics applications. The surface plasmon polaritons (SPP) exited by light on metallic nano grooves arrays (NGA) and nanowires (NWs), play a role of an intermediary between photonics and electronics. We report on the experimental demonstration of polarization controlled SPP propagation, leading to tailored directional coupling in a periodic plasmonic NGAs and NWs. The SPP emission and propagation, in Au NGAs and Au NWs is modulated by the incident light polarization. Our results establish a basis for the developments of innovative optical devices, which are useful in telecommunications and other nanophotonic devices.
{"title":"Polarization controlled emission on gold nanogrooves and nanowires","authors":"D. Rajesh, Ziv Glasser, Y. Gorodetski, S. Sternklar, D. Cheskis","doi":"10.1109/ICSEE.2018.8646132","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646132","url":null,"abstract":"The rapid growing interest in the field of plasmonics comes from advance nanotechnologies involving nanophotonics applications. The surface plasmon polaritons (SPP) exited by light on metallic nano grooves arrays (NGA) and nanowires (NWs), play a role of an intermediary between photonics and electronics. We report on the experimental demonstration of polarization controlled SPP propagation, leading to tailored directional coupling in a periodic plasmonic NGAs and NWs. The SPP emission and propagation, in Au NGAs and Au NWs is modulated by the incident light polarization. Our results establish a basis for the developments of innovative optical devices, which are useful in telecommunications and other nanophotonic devices.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125737122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646070
Hagai Barmatz, Dana Klein, Y. Vortman, Sivan Toledo, Y. Lavner
Animal communication and specifically acoustic communication is in the focus of ecological and biological research. With the advancement of monitoring technology, a vast amount of acoustic recordings of birds is continuously accumulated. As manual segmentation and annotation of this data is impractical, development of efficient algorithms for accurate detection, classification and segmentation of birdsong is therefore a prerequisite for further analysis. In this study we present an algorithm for automatic segmentation and parameters estimation of one type of bird vocalization, namely, the trill song. The algorithm is based on computing the short-time variance of the fundamental frequency derivative of bird acoustic signal for initial detection of syllables. The boundaries of each syllable are consequently obtained using a Gaussian smoothed short-time energy function and an adaptive threshold based on the energy envelope. The performance of the algorithm was evaluated using a comparison to human expert segmentation, as well as to ground-truth values of synthetic trills produced by the Harmonic + Noise model. A correct detection rate of more than 95% was yielded for SNR levels of -5 dB or higher for signals with additive colored noise, and for signals with additive white Gaussian noise more than 92% was obtained for SNR>-5dB. In addition, a high correlation between the automatic segmentation and that of a human expert was exemplified.
{"title":"Segmentation and Analysis of Bird Trill Vocalizations","authors":"Hagai Barmatz, Dana Klein, Y. Vortman, Sivan Toledo, Y. Lavner","doi":"10.1109/ICSEE.2018.8646070","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646070","url":null,"abstract":"Animal communication and specifically acoustic communication is in the focus of ecological and biological research. With the advancement of monitoring technology, a vast amount of acoustic recordings of birds is continuously accumulated. As manual segmentation and annotation of this data is impractical, development of efficient algorithms for accurate detection, classification and segmentation of birdsong is therefore a prerequisite for further analysis. In this study we present an algorithm for automatic segmentation and parameters estimation of one type of bird vocalization, namely, the trill song. The algorithm is based on computing the short-time variance of the fundamental frequency derivative of bird acoustic signal for initial detection of syllables. The boundaries of each syllable are consequently obtained using a Gaussian smoothed short-time energy function and an adaptive threshold based on the energy envelope. The performance of the algorithm was evaluated using a comparison to human expert segmentation, as well as to ground-truth values of synthetic trills produced by the Harmonic + Noise model. A correct detection rate of more than 95% was yielded for SNR levels of -5 dB or higher for signals with additive colored noise, and for signals with additive white Gaussian noise more than 92% was obtained for SNR>-5dB. In addition, a high correlation between the automatic segmentation and that of a human expert was exemplified.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126828589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646205
David Levy, A. Reichman, D. Wulich
Filter Bank Multi Carrier (FBMC) is considered as promising candidate solution to the air interference problem in the fifth-generation communication (5G). Since the performance of multicarrier transmission is affected by peak to average power ratio (PAPR) therefore, research on PAPR reduction methods is essential. The paper presents the effect of the simplest method for reduction the PAPR for FBMC modulation by using the iterative clipping and filtering (ICF) method. A significant improvement in PAPR reduction can be obtained with a modest complexity and low degradation in Bit Error Ratio (BER).
{"title":"Peak to Average Power Ratio Reduction for Filter Bank Multicarrier Modulation using Iterative Clipping and Filtering","authors":"David Levy, A. Reichman, D. Wulich","doi":"10.1109/ICSEE.2018.8646205","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646205","url":null,"abstract":"Filter Bank Multi Carrier (FBMC) is considered as promising candidate solution to the air interference problem in the fifth-generation communication (5G). Since the performance of multicarrier transmission is affected by peak to average power ratio (PAPR) therefore, research on PAPR reduction methods is essential. The paper presents the effect of the simplest method for reduction the PAPR for FBMC modulation by using the iterative clipping and filtering (ICF) method. A significant improvement in PAPR reduction can be obtained with a modest complexity and low degradation in Bit Error Ratio (BER).","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126297402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646018
O. Barzilai, Nadav Voloch, Alon Hasgall, O. L. Steiner
Smart devices and their connections to the Internet of Things (IoT) have been the subject of many papers in the past decade. One of the transportation subjects of IoT is a smart junction. This research deals with the case of this junction, where several cars approach the intersection from various directions, and a smart traffic light must decide about the time intervals of RED and GREEN in each direction, with our novel approach that is based not only on the number of vehicles in each lane, but also on other factors such as the type of vehicles (e.g. emergency vehicles), and the social characteristics of the passengers (e.g. a handicapped person, a student who is late for an exam). Those factors will be gleaned from the IoT network amongst cars, traffic lights, individuals, municipality data, and more. Once those priorities have been examined, they are fed into the algorithm we have devised, and outputted as a timing schedule for the different sides of the intersection, taking also into consideration the cars physical attributes such as length and speed. In this paper we present the algorithm, the prioritizing research, its implementation in the algorithm and our experimental results.
{"title":"Real life applicative timing algorithm for a smart junction with social priorities and multiple parameters","authors":"O. Barzilai, Nadav Voloch, Alon Hasgall, O. L. Steiner","doi":"10.1109/ICSEE.2018.8646018","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646018","url":null,"abstract":"Smart devices and their connections to the Internet of Things (IoT) have been the subject of many papers in the past decade. One of the transportation subjects of IoT is a smart junction. This research deals with the case of this junction, where several cars approach the intersection from various directions, and a smart traffic light must decide about the time intervals of RED and GREEN in each direction, with our novel approach that is based not only on the number of vehicles in each lane, but also on other factors such as the type of vehicles (e.g. emergency vehicles), and the social characteristics of the passengers (e.g. a handicapped person, a student who is late for an exam). Those factors will be gleaned from the IoT network amongst cars, traffic lights, individuals, municipality data, and more. Once those priorities have been examined, they are fed into the algorithm we have devised, and outputted as a timing schedule for the different sides of the intersection, taking also into consideration the cars physical attributes such as length and speed. In this paper we present the algorithm, the prioritizing research, its implementation in the algorithm and our experimental results.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130062379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646294
Samah Khawaled, Mohamad Khateeb, Hadas Benisty
Existing sound retrieval systems are mostly based on a textual query. Using text to describe a sound signal is not intuitive and is often inaccurate due to subjective impression of the user; different people may use different words to describe the same sound which makes theses system complex to design and unintuitive to use. Vocal imitation, however, is the most natural human way to describe a sound. In this paper we consider a newly rising approach for sound retrieval based on vocal imitations, where the user records himself imitating the desired sound, and the system retrieves a ranked list of the most similar sounds in the dataset. In this work we represent sound signals using histograms, obtained with respect to a Gaussian Mixture Model (GMM), representing the spectral domain. This recently proposed approach was successfully applied for word representation in a keyword spotting task. Having a fixed length representation for vocal imitation signals allows us to train a robust classifier using support vector machine (SVM). Given a test imitation signal, we apply the classifier and use the output score to rank the retrieved signals, based on a majority vote. Our simulation results show that the proposed system yields a more accurate ranking compared with other existing solutions.
{"title":"Audio Retrieval By Voice Imitation","authors":"Samah Khawaled, Mohamad Khateeb, Hadas Benisty","doi":"10.1109/ICSEE.2018.8646294","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646294","url":null,"abstract":"Existing sound retrieval systems are mostly based on a textual query. Using text to describe a sound signal is not intuitive and is often inaccurate due to subjective impression of the user; different people may use different words to describe the same sound which makes theses system complex to design and unintuitive to use. Vocal imitation, however, is the most natural human way to describe a sound. In this paper we consider a newly rising approach for sound retrieval based on vocal imitations, where the user records himself imitating the desired sound, and the system retrieves a ranked list of the most similar sounds in the dataset. In this work we represent sound signals using histograms, obtained with respect to a Gaussian Mixture Model (GMM), representing the spectral domain. This recently proposed approach was successfully applied for word representation in a keyword spotting task. Having a fixed length representation for vocal imitation signals allows us to train a robust classifier using support vector machine (SVM). Given a test imitation signal, we apply the classifier and use the output score to rank the retrieved signals, based on a majority vote. Our simulation results show that the proposed system yields a more accurate ranking compared with other existing solutions.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131241822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8646048
I. Goldshtein, M. Averbukh
Electrification of Israel railroads is a successful project being realized during present time. Among the well-known advantages of electric train exploitation are high energetic efficiency, regenerative breaking, diminished pollution, flexibility of traffic control and improved transportation dynamics. However, the use of electric train is accompanied with some specific hurdles caused by significantly stochastic power flows. While in transit between stations an electric train has different phases of movement, during some consuming energy, but from time to time throughout braking processes they become generators transmitting energy back into the electric grid. This circumstance may produce voltage instability in distribution lines, which should be kept inside permissible limits to allow normal operation of electric equipment. Tap-changers on distribution transformers considered for a voltage regulation have sluggish response of ~7-8 sec. Therefore, fast changes of power stream can cause significant voltage deviations. If the voltage overcome explicit allowable level a trigger of a protection system is engendered disconnecting vehicles from a grid. The last causes extremely dangerous detriments and should be maximally prevented.Rapid and considerable changes in train power consumption, in addition may cause network frequency instability which in turn can violate electricity supply.Present article provides an original examination of the future stability of network frequency and distribution voltage which may be assumed when 420 km of Israel railroads will be electrified in the following 5–10 years. For such study special algorithm based on simulation approach was developed and applied. Predicting scenarios for frequency and distribution lines voltage control are represented below in the following text.
{"title":"Electrification Israel Railroads: Network Frequency Instability and Challenges of Distribution Voltage Control","authors":"I. Goldshtein, M. Averbukh","doi":"10.1109/ICSEE.2018.8646048","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8646048","url":null,"abstract":"Electrification of Israel railroads is a successful project being realized during present time. Among the well-known advantages of electric train exploitation are high energetic efficiency, regenerative breaking, diminished pollution, flexibility of traffic control and improved transportation dynamics. However, the use of electric train is accompanied with some specific hurdles caused by significantly stochastic power flows. While in transit between stations an electric train has different phases of movement, during some consuming energy, but from time to time throughout braking processes they become generators transmitting energy back into the electric grid. This circumstance may produce voltage instability in distribution lines, which should be kept inside permissible limits to allow normal operation of electric equipment. Tap-changers on distribution transformers considered for a voltage regulation have sluggish response of ~7-8 sec. Therefore, fast changes of power stream can cause significant voltage deviations. If the voltage overcome explicit allowable level a trigger of a protection system is engendered disconnecting vehicles from a grid. The last causes extremely dangerous detriments and should be maximally prevented.Rapid and considerable changes in train power consumption, in addition may cause network frequency instability which in turn can violate electricity supply.Present article provides an original examination of the future stability of network frequency and distribution voltage which may be assumed when 420 km of Israel railroads will be electrified in the following 5–10 years. For such study special algorithm based on simulation approach was developed and applied. Predicting scenarios for frequency and distribution lines voltage control are represented below in the following text.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131778604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1109/ICSEE.2018.8645982
Hanna Abo Hanna, Loai Danial, Shahar Kvatinsky, Ramez Daniel
A memristor is a nano-scale two-terminal stochastic electronic device. This paper proposes functional analogies between biochemical reactions and memristive devices. It shows that memristors can mimic biochemical reactions and gene networks efficiently and capture both deterministic and stochastic dynamics at the nano-scale level. We present different abstraction models and voltage-controlled resistive switching circuits that inherently model the activity of genetic circuits with low signal-to-noise ratio (SNR). These findings constitute a milestone for cell-inspired circuit design with noise-tolerance and energy-efficiency features, which can provide a fast and simple emulative framework for studying arbitrary large-scale biological networks in systems and synthetic biology.
{"title":"Memristors as Artificial Biochemical Reactions in Cytomorphic Systems","authors":"Hanna Abo Hanna, Loai Danial, Shahar Kvatinsky, Ramez Daniel","doi":"10.1109/ICSEE.2018.8645982","DOIUrl":"https://doi.org/10.1109/ICSEE.2018.8645982","url":null,"abstract":"A memristor is a nano-scale two-terminal stochastic electronic device. This paper proposes functional analogies between biochemical reactions and memristive devices. It shows that memristors can mimic biochemical reactions and gene networks efficiently and capture both deterministic and stochastic dynamics at the nano-scale level. We present different abstraction models and voltage-controlled resistive switching circuits that inherently model the activity of genetic circuits with low signal-to-noise ratio (SNR). These findings constitute a milestone for cell-inspired circuit design with noise-tolerance and energy-efficiency features, which can provide a fast and simple emulative framework for studying arbitrary large-scale biological networks in systems and synthetic biology.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129304922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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