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Selective signal Sample Forwarding for Receive Diversity in Energy-Constrained sensor Networks

Selective Signal Sample Forwarding for Receive Diversity in ...

引用

ieee International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd workshop on Optical Wireless Communications (OWC)

作者： Nabeel, Muhammad Bloessl, Bastian Dressler, Falko Univ Paderborn Heinz Nixdorf Inst Paderborn Germany Univ Paderborn Dept Comp Sci Paderborn Germany

ISBN: (纸本)9781467389990

Receive diversity increases the reliability and robustness of ultra-low powerWireless sensor Networks (WSNs) by using spatially separated antennas without modifying the physical layer. We consider a distributed ground network in the wild to track bats in their natural habitat. The bats are equipped with a sensor node of only 2 g that limits the energy budget available for communication. In this work, we exploit the distributed nature of the ground network to employ diversity combining, i.e., we use the ground nodes as a geographically distributed multi-antenna array. However, this causes several research challenges given the limited bandwidth between nodes and the need for accurate synchronization to combine signal copies constructively at a central node. Sending all signal samples from all ground nodes to the central node is prohibitive due to the required data rates in the network. As a novel concept, we propose a system that only forwards selected signal samples belonging to a packet with high probability. We study the performance in simulations as well as in a testbed using a Software Defined Radio (SDR) prototype implementation. Our results clearly indicate a substantial performance gain while keeping the data rate in the ground network in a feasible range.

关键词： Diversity reception Receivers Diversity methods Mobile nodes Bandwidth Synchronization

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Tactile sensor array signal and data processing based on information fusion

Tactile sensor array signal and data processing based on inf...

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3rd International Conference on Innovative Computing Information and Control, ICICIC'08

作者： Guo, Bing Qin, Lan Liu, Jun Liu, Zhihui Key Lab. of Optoelectronic Technology and Systems Ministry of Education Chongqing University Chongqing 400030 China

ISBN: (纸本)9780769531618

It developed a sort of tactile sensor array system that built in various shapes and provided a wide range of spatial resolution. The sensor system built a demonstration system in lab and developed algorithms to process the large amount of tactile data. The efficient fusion of data from different sensors would enable the robot to respond promptly in dealing with the "real world". The confidence distance measure was used as fusion measure of information fusion. The useful fused data found by confidence distance matrix and relation matrix. Finally, the optimal fused data was given by maximum principle and maximum likelihood method. Using algorithm based information fusion, the influence of single sensor cell uncertainty errors could be avoid, surface depth data measure and image reconstruction precision of object profile could be improved. © 2008 ieee.

关键词： Maximum likelihood

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Sonar interpretation learned from laser data 3

Sonar interpretation learned from laser data

引用

3rd European workshop on Advanced Mobile Rob.ots, Eurobot 1999

作者： Enderle, Stefan Kraetzschmar, Gerhard Sablatnog, Stefan Palm, Gunther Neural Information Processing Department University of Ulm Germany

ISBN: (纸本)0780356721

sensor interpretation in mobile robots often involves an inverse sensor model, which generates hypotheses on specific aspects of the robot's environment based on current sensor data. Building inverse sensor models for sonar sensor assemblies is a particularly difficult problem that has received much attention in the past few years. A common solution is to train neural networks using supervised learning. However, large amounts of training data are typically needed, consisting, for example, of scans of recorded sonar data which are labeled with manually constructed teacher maps. Obtaining these training data is an error-prone and time-consuming process. We suggest that it can be avoided if an additional sensor, like a laser scanner, is also available which can act as the feeding signal. We have successfully trained inverse sensor models for sonar interpretation using laser scan data. In this paper, we describe the procedure we used and the results we obtained. © 1999 ieee.

关键词： Sonar

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On-chip Pixel Reconstruction using Simple CNN for Sparsely Read CMOS Image sensor 3

On-chip Pixel Reconstruction using Simple CNN for Sparsely R...

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ieee 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Kisku, Wilfred Kaur, Amandeep Mishra, Deepak Indian Inst Technol Dept Elect Engn Jodhpur Rajasthan India Indian Inst Technol Dept Comp Sci & Engn Jodhpur Rajasthan India

ISBN: (纸本)9781665419130

CMOS image sensors have gained popularity due to low power consumption, high speed and their ability to scale to smaller sizes. These factors can further be improved by either improving the circuitry of the imager or by enhancing the processing capabilities of the entire imaging system through on-chip processing of the pixel information. One such improvement is to read only a small fraction of the pixel array information and reconstruct the original information from it. The on-chip prediction of the unread pixels to reconstruct the acquired image is still an open problem. Here we propose a solution to the problem which relies on on-chip implementation of simple convolutional neural network (CNN) for pixel prediction and image reconstruction. The system strives to selectively read only a minimal number of pixels (10% to 15%), while skipping the rest. This attributes to a considerable saving on power and checks the issue of latency at the ADC. This selective process in reading of only few pixels generates a sparse image signal. The proposed network is trained to reconstruct the estimation of the actual image from the sparse set. The hardware accelerator that incorporates the CNN model also considers hardware limitations and constraints such as power consumption and latency. The PSNR achieved for the SiDCNet variant with SqueezeNet achieves for test images is similar to 30 dB for 85% of pixels skipped, and the quantized model does not lose much in PSNR.

关键词： Deep Learning Convolutional Neural Networks Compressed Sensing System On-Chip Image sensors

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BSS for improved interference estimation for Blind speech signal Extraction with two microphones

BSS for improved interference estimation for Blind speech si...

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ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Yuanhang Zheng Klaus Reindl Walter Kellermann Multimedia Communications and Signal Processing University of Erlangen Nuremberg Erlangen Germany

ISBN: (纸本)9781424451791;9781424451807

Blind source extraction (BSE) as desirable for acoustic cocktail party scenarios requires estimates for the target or interfering signals. Conventional single-channel approaches for obtaining the interference estimate rely on noise and interference estimates during absence of the target signal. For multichannel approaches using multiple microphone signals, a separation of simultaneously active target and interference signals becomes possible if the positions of the target and interfering sources are known. We propose a new method which exploits directional BSS (blind source separation with a geometric constraint) to estimate the interfering speech sources and diffuse background noise jointly and blindly. Herewith we can effectively deal with the underdetermined BSS scenario (more point sources than sensors) in reverberant environments and can even allow for additional babble noise in the background.

关键词： Interference Microphones Source separation Speech enhancement Background noise sensor arrays MIMO signal processing Blind source separation array signal processing

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Digitization of the Distribution Grid to Support e-Mobility Charging Infrastructure 3

Digitization of the Distribution Grid to Support e-Mobility ...

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3rd ieee International workshop on Metrology for Automotive (ieee MetroAutomotive)

作者： vom Boegel, Gerd Essingholt, Felix Bennertz, Bernhard Grenter, Thorben Fraunhofer IMS Busines Unit Ind Duisburg Germany Fraunhofer IMS Smart Sensor Syst Duisburg Germany Fraunhofer IMS Embedded Software & AI Duisburg Germany

ISBN: (纸本)9798350321876

The article addresses a subproject of the Energy ECS project [1], in which the development and realization of suitable components for condition monitoring of electrical distribution grids is carried out. By means of suitable sensor systems, communication and IT infrastructure components, relevant information on network infrastructure elements at neuralgic points is collected, aggregated and communicated. This information can be used directly for a highly dynamic grid-serving control of grid components to ensure a robust and efficient use of the distribution grid. The project makes a direct contribution to the digitization of distribution grids and thus contributes to the successful integration of decentralized generators and electromobility. The main objective of the subproject is the development and realization of energy-autonomous sensor systems for recording the status of relevant components of a low-voltage distribution network. The work to be carried out includes sensor principles as well as the field of energy harvesting or the field of sensor signal processing.

关键词： smart grid monitoring self-sufficient sensor LPWAN controlled charging infrastructure

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3d architecture and replaceable layers for label-free dna biochips

3d architecture and replaceable layers for label-free dna bi...

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3rd International workshop on Advances in sensors and Interfaces, IWASI 2009

作者： Temiz, Yuksel Carrara, Sandro Cavallini, Andrea Leblebici, Yusuf Micheli, Giovanni De. CH-1015 Lausanne Switzerland

ISBN: (纸本)9781424447091

Recent advances in bio-sensing technologies have led to design of bio-sensor arrays for rapid identification and quantification of various biological agents such as drugs, gene expressions, proteins, cholesterol, fats, etc. Various dedicated sensing arrays are already available commercially to monitor some of these compounds in a sample. However, monitoring the simultaneous presence of multiple agents in a sample is still a challenging task. Multiple agents may often attach to the same probes on an array which makes it difficult to design a chip that can distinguish such agents (leading to low specificity). Thus, sophisticated algorithms for targets identification need to be implemented in biochip in order to maximize the number of distinguishable targets in the samples. The proposed algorithms are also required to introduce sophisticated signal processing and more intelligence on-chip. Dealing with these new processing and information technology demands constraints also require more innovative approaches towards hybrid integration technologies. To address such new demands, we discuss in this paper an innovative 3D-integrated bio-chips especially dedicated to label-free DNA detection.

关键词： Biochips

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MIMO Channel identification using the DOA and DOD estimation 3

MIMO Channel identification using the DOA and DOD estimation

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3rd International workshop on RFID and Adaptive Wireless sensor Networks (RAWSN)

作者： Hachad, L. Mrabti, F. Zouak, M. Mrabti, M. Fac Sci & Technol SSC Lab Fes Morocco Natl Sch Appl Sci Lab SIS Fes Morocco

ISBN: (纸本)9781467380966

Channel identification finds direct application in the growing field of mobile wireless communications. In this paper, we address this problem in the context of multi-users: multiple-input multiple-output (MIMO) channels. To avoid scheduling at the reception we will proceed to a source separation (DOA and DOD estimation) then we will deduct the channel parameters. The estimation of the directions of departure (DOD) and directions of arrival (DOA), is based on the strong algebraic structure of tensor algebra: PARAFAC method. The Second Order Statistics (SOS) are used for the estimation of the impulse response's parameters of the MIMO channel. The performance of the proposed method will be proved by the simulation study.

关键词： array processing Channel estimation MIMO (Multi Input Multi-Output) Tensor Algebra

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Optimal sensor placement for damage detection

Optimal sensor placement for damage detection

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3rd European workshop on Structural Health Monitoring 2006

作者： Krawczuk, M. Kudela, R. Ostachowicz, W. Palacz, M. Zak, A. Polish Academy of Sciences IFFM Fiszera 14 80-231 Gdansk Poland Technical University of Gdansk Faculty of Electrical and Control Engineering Narutowicza 11/12 80-952 Gdansk Poland Gdynia Maritime University Faculty of Navigation Al. Zjednoczenia 3 81-345 Gdynia Poland

ISBN: (纸本)1932078630

In this study a damage identification approach has been developed for an aluminium plate with damage. A real time diagnostic system has been established Propagating Lamb waves have been introduced. The proposed technique uses distributed piezoelectric transducers to generate and monitor the wave changes due to damage occurrence. In presented approach the sensors have been deployed in arrays. Two different configurations have been tested. With proposed methodologies the sensor information has been combined with adequate signal processing in order to obtain a reliable damage location indication. Therefore a minimal number of sensors needed for proper damage location estimation has been established. The number of sensors needed is strongly connected with the proposed shape of sensor array.

关键词： Damage detection

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Neural network-based helicopter gearbox health monitoring system 3

Neural network-based helicopter gearbox health monitoring sy...

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1993 3rd ieee-SP workshop on Neural Networks for signal processing, NNSP 1993

作者： Kazlas, P.T. Monsen, P.T. Leblanc, M.J. Sensor and Communication Electronics Division Charles Stark Draper Laboratory 555 Technology Square CambridgeMA02139 United States

ISBN: (纸本)0780309286

The results of two neural hardware implementations of a helicopter gearbox health monitoring system (HMS) are summarized. The first hybrid approach and implementation to fault diagnosis is outlined, and results are summarized using three levels of fault characterization: Fault detection (fault or no fault), classification (hear or bearing fault), and identification (fault sub-classes). Initial hardware results compare well with previously published software simulations. The second all-analog implementation exploits the ability of analog neural hardware to compute the discrete Fourier transform (DFT) as a preprocessor to a neural classifier. © 1993 ieee.

关键词： Fault detection

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