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A novel recovery algorithm of time encoded signals

BMC Neuroscience 2013年第1期14卷 1-2页

作者： Dorian Florescu Daniel Coca Department of Automatic Control and Systems Engineering University of Sheffield Sheffield South Yorkshire S1 3JD UK

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A Novel Surface recovery algorithm for Dual Wavelength White LED in Vertical Scanning Interferometry (VSI)

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SENSORS 2020年第18期20卷 5225.-5225.页

作者： Zhu, Linlin Dong, Yuchu Li, Zexiao Zhang, Xiaodong Tianjin Univ Ctr MicroNano Mfg Technol State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China

The two peaks characteristic of yellow and blue light in the spectrum of dual-wavelength white light emitting diodes (LEDs) introduce distinctive features to the interference signal of white light scanning interferometry (WLSI). The distinctive features are defined as discontinuities, so that the fringe contrast function cannot be modeled as a single Gaussian function, and causes the interferogram to have uneven distribution of fringes of different orders in the scanning interferometer. This phenomenon leads to the low accuracy of the zero-order fringe position in the envelope calculation, which affects the repeatability and accuracy of the interferometry. This paper proposes a new surface recovery algorithm based on the Hilbert phase envelope and adjacent reference points calculation, which can effectively overcome the influence of the discontinuous signal of dual-wavelength LED white light interference on the three-dimensional reconstruction of WLSI measurements. The reliability of the algorithm is verified by experiments, and the measurement accuracy of LED WLSI system is evaluated.

关键词： vertical scanning interferometry dual wavelength white LED recovery algorithm

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A Novel recovery algorithm for Multi-link Failures in Spectrum-Elastic Optical Path Networks

A Novel Recovery Algorithm for Multi-link Failures in Spectr...

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Conference on Network Architectures, Management, and Applications IX

作者： Chen, Bowen Zhang, Jie Zhao, Yongli Lv, Chunhui Zhang, Wei Gu, Yuan Huang, Shanguo Gu, Wanyi Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

ISBN: (纸本)9780819489586

In this paper, a novel survivable algorithm with dynamic load balancing shared-path protection is proposed, named DLBSPP algorithm, in spectrum-elastic optical path networks (SLICE). To tolerate multi-link failures in SLICE, traffic self-adaptive restoration (TSAR) mechanism is adopted to restore the traffic affected by the failures. Simulation results show that, compared with the conventional SPP algorithm, DLBSPP algorithm has lower blocking probability (BP), better spectrum utilization ratio (SUR) and higher failure restoration ratio (FRR).

关键词： SLICE multi-link failures restoration recovery algorithm dynamical load balancing

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Rapid calculation of bistatic scattering problems based on bayesian compressive sensing

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ELECTROMAGNETICS 2025年第4期45卷 320-333页

作者： Wang, Zhonggen Sun, Longhui Nie, Wenyan Sun, Yufa Dong, Dai Liu, Yang Anhui Univ Sci & Technol Sch Elect & Informat Engn Huainan 232001 Peoples R China HuaiNan Normal Univ Sch Mech & Elect Engn Huainan Peoples R China Anhui Univ Sch Elect & Informat Engn Hefei Peoples R China

In this paper, in order to accelerate the solution of the three-dimensional target scattering problems, bayesian compressive sensing (BCS) combined with high-order characteristic basis functions (HCBFs) is proposed. Unlike the traditional compressive sensing (CS) combined with CBFs method, the main improvements of our work are twofold: First, by utilizing HCBFs instead of traditional CBFs, not only the construction of the sparse basis is accelerated, but also the computational accuracy is improved. Second, comparing to CS using the orthogonal matching pursuit recovery algorithm, BCS requires fewer iterations and takes less time in recovering sparse signals. Numerical calculations show that the new method not only accelerates the solution time but also improves the computational accuracy.

关键词： Bayesian compressive sensing characteristic basis functions recovery algorithm

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Association Rule Mining Based algorithm for recovery of Silent Data Corruption in Convolutional Neural Network Data Storage

Association Rule Mining Based Algorithm for Recovery of Sile...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Ramzanpour, Mohammadreza Ludwig, Simone A. North Dakota State Univ Dept Comp Sci Fargo ND 58105 USA

ISBN: (纸本)9781728125473

Embedded systems are finding their way into almost every aspects of our daily life from mp3 players and console games to the mobile phones. Different Artificial Intelligence (AI) based applications are commonly utilized in embedded systems from which computer vision based approaches are included. The demand for higher accuracy in computer vision applications is associated with the increased complexity of convolutional neural networks and the storage requirement for saving pre-trained networks. Different factors can lead to the data corruption in the storage units of the embedded systems, which can result in drastic failures due to the propagation of the errors. Hence, the development of software-based algorithms for the detection and recovery of data corruption is crucial for improvement and failure-prevention of embedded systems. This paper proposes a new algorithm for the recovery of the data in the case of single event upset (SEU) error. The association rule mining based algorithm will be used to find the probability of the corruption in each of the bits. The recovery algorithm was tested on four different pre-trained ResNet (ResNet32 and ResNet110 at two different accuracy levels each) and the best recovery rate of 66% was found in the most complex scenario, i.e., random bit corruption. However, for the special cases of SEU errors, e.g. error in the frequently repeated bits, the recovery rate was found to be perfect with a value of 100%.

关键词： Single event upset Silent data corruption Association rule mining recovery algorithm

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Wavefront recovery Fourier-based algorithm used in a Vectorial Shearing Interferometer

Wavefront recovery Fourier-based algorithm used in a Vectori...

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Conference on Infrared Remote Sensing and Instrumentation XXI

作者： Bravo-Medina, Beethoven Garcia-Torales, G. Legarda-Saenz, Ricardo Flores, Jorge L. Univ Guadalajara Dept Elect Guadalajara 44840 Jalisco Mexico

ISBN: (纸本)9780819497178

Vectorial Shearing Interferometer is able to select variable shear and tilt along any wavefront direction. This system is self-referenced and with variable sensibility. We proposed this instrument to measure a phase object without rotational symmetry. Phase recovery is implemented by a Fourier-based algorithm and spatial unwrapping methods. We show results emphasizing the advantage in the easier selection of fringe density and directional derivative orientation for a specific optical element.

关键词： wavefront shearing interferometer recovery algorithm

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Analysis of three dimensional recovery algorithms' influence on the ranging accuracy of Gm-APD Ladar 10

Analysis of three dimensional recovery algorithms' influence...

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10th International Conference on Information Optics and Photonics

作者： Gao, Shang Sun, Jianfeng Jiang, Peng Liu, Di Zhou, Xin Fu, Hongming Wang, Penghui Harbin Inst Technol Natl Key Lab Sci & Technol Tunable Laser Inst Opto Elect Harbin 150001 Heilongjiang Peoples R China Beijing Electro Mech Engn Inst Beijing 100074 Peoples R China China Airborne Missile Acad Luoyang 471009 Peoples R China

ISBN: (纸本)9781510625808

Geiger-mode Avalanche Photo Diode(Gm-APD) Ladar is a probabilistic device outputting three dimensional(3D) images based on the multi-frame imaging statistics, which makes the 3D recovery algorithm one of the key techniques of imaging system. Besides, performance of algorithm plays a crucial role in improving recovery quality of 3D images. This paper researches three 3D algorithms based on histograms, containing peak-selecting algorithm, range-selecting algorithm and Gaussian fitting algorithm. Firstly, the triggered model of Gm-APD is analyzed based on the work timing sequence and imaging theory of Gm-APD Ladar. Meanwhile, the recovery principles of three algorithms are analyzed and clarified. Secondly, two evaluation criterions, average range error and accuracy of range recovery, are raised to evaluate range accuracy. Finally, range images are obtained with above three algorithms in statistics of different frames, based on original data obtained from 64 x 64 Gm-APD Ladar imaging experiment. With the three construction algorithms, the result shows that the range accuracy of recovery range images improves and converges to 0.2 similar to 0.3m with the increment of number of frames participating in the statistics, and the accuracy of range recovery can be up to 90%. In low frame numbers, the range accuracy of recovery range profile is worst with peak-selecting algorithm, and the average range error with range-selecting algorithm performs best while accuracy of range recovery with Gaussian fitting algorithm is highest among all algorithms. The result has important guiding significance for the choice of recovery algorithm under different requests.

关键词： Geiger-mode Avalanche Photo Diode Ladar recovery algorithm average range error accuracy of range recovery

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Comparative Study on recovery algorithms for Solving Electromagnetic Scattering Problems by Compressive Sensing 11

Comparative Study on Recovery Algorithms for Solving Electro...

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11th International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Hou, Xinli Chen, Mingsheng Zhu, Yanyan Cao, Xinyuan Zhao, Hui Wu, Xianliang Hefei Normal Univ Sch Elect & Informat Engn Hefei 230601 Peoples R China Anhui Univ Sch Elect & Informat Engn Hefei 230039 Peoples R China

ISBN: (纸本)9781509047437

A new incident source is formed based on compressive sensing (CS) theory, in which much information from different incident angle is included. By solving the integral equations under this new incident source, one can obtain the measurements of the induced currents without calculating the problems with a finer angle increment. Especially, different recovery algorithms of CS are studied as used to solve electromagnetic problems over a wide incident angle. Numerical simulation results have shown that the efficiency of the new method can be greatly improved, since the total number of measurements required can be reduced drastically by choosing suitable recovery algorithm.

关键词： compressive sensing method of moments recovery algorithm electromagnetic scattering

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COMPARING THE PERFORMANCE OF recovery algorithmS FOR ROBUST FACE RECOGNITION

COMPARING THE PERFORMANCE OF RECOVERY ALGORITHMS FOR ROBUST ...

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International Conference on Interfaces and Human Computer Interaction / International Conference on Game and Entertainment Technologies / International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing

作者： Ghofrani, Sedigheh Alikiaamiri, Seyedramin Khorasani, Mehran Islamic Azad Univ South Tehran Branch Elect & Elect Engn Dept Tehran Iran

ISBN: (纸本)9789898533388

The problem of automatically recognizing human faces from the facial images under varying expression and illumination is still attractive. The sparse signal representation is a new topic for object classification and face recognition. Implementing the sparse representation needs using a proper reconstruction algorithm to recover the sparse signal as well. In this paper, the performance of three greedy algorithms named matching pursuit (MP), orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP) and two l(1) -minimization algorithms named primal-dual interior-point (PDIP) and Homotopy are compared according to achieved accuracy, consuming time, and the number of iterations. For this purpose, three well known datasets named, AR, Extended Yale B and Essex University are used.

关键词： Face Recognition Sparse Representation recovery algorithm

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Compressed sensing: a new approach to analyze the recovery algorithms Based on UWB channel estimation

Compressed sensing: a new approach to analyze the recovery a...

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IEEE International Conference on Computing, Management and Telecommunications (ComManTel)

作者： Nguyen Thanh Son Nguyen Vu Quynh Pham Van Toan Le Phuong Truong LacHong Univ Dept Electromech & Elect Bien Hoa Dong Nai Provin Vietnam

ISBN: (纸本)9781479929030

Compressed Sensing (CS) is a new mathematical concept, which can reconstruct the original signal accurately with lower Nyquist sampling. Besides, multipath arrivals in an Ultra-wideband (UWB) channel have a long time intervals between clusters and rays where the signal takes on zero or negligible values. It is precisely this signal sparsity of the impulse response of the UWB channel that is suitable for the application of Compressed Sensing theory. However, these multipath arrivals mainly depend on the channel models that generate different sparse levels (low-sparse or high-sparse) of the UWB channels according to which, the authors have analysed and chosen the best recovery algorithms which are suitable to the sparse level for each type of channel environment. Criteria for evaluating the algorithms are based on computational complexity, ability to reduce the sampling rate and processing time. In addition, the results of this study are an open topic for further research aimed at creating a optimal algorithm specially for application of CS based UWB systems.

关键词： Compressed sensing sparse level recovery algorithm multipath channel ultra-wideband channel model

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