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Power efficient low latency architecture for decoder: Breaking the ACS bottleneck

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2019年第9期47卷 1513-1528页

作者： Radha, Subramanyam Shylu, David Sundararaj Nagabushanam, Perattur Karunya Inst Technol & Sci Dept Elect Sci ECE Programme Coimbatore Tamil Nadu India

Viterbi decoder (VD) is the majority used decoder for convolutional codes which play a role in WLAN and WSN applications. The trellis in VD needs proper analysis to calculate the metric at each stage to obtain a shortest path from every state to the next state. Existing techniques in VD design are namely (a) pipelined architecture, (b) modular ACS and buffers technique, and (c) quasi cyclic trellis technique. The key challenge of the VD trellis circuit is to attain high throughput and better latency performance with low power consumption without affecting hardware complexity of VD. This paper presents several of conventional methods used in VD. We also proposed a new method for VD with K the constraint length as multiple of M, the radix in trellis to calculate the shortest survival path to travel in trellis. The proposed VD is simulated using Xilinx. Use of a trace back approach in the proposed Viterbi decoder with capacitive and resistive feedback yields better throughput, latency, and power consumption with respect to other techniques. The static power outputs obtained in RE, shift update, and selective update methods using Libero IDE are also compared.

关键词： add-select-compare (ACS) maximum likelihood algorithm path metric pipeline architecture Viterbi decoder (VD)

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Forest restoration monitoring through digital processing of high resolution images

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ECOLOGICAL ENGINEERING 2019年 127卷 178-186页

作者： Reis, Bruna Paolinelli Martins, Sebastiao Venancio Fernandes Filho, Elpidio Inacio Sarcinelli, Tathiane Santi Gleriani, Jose Marinaldo Leite, Helio Garcia Halassy, Melinda Univ Fed Vicosa Forest Engineer Dept Ave PH Rolfs S-N BR-36570000 Vicosa MG Brazil Univ Fed Vicosa Soil Dept Ave PH Rolfs S-N BR-36570000 Vicosa MG Brazil Fibria Celulose SA Meio Ambiente Florestal Rodovia Aracruz Barra do Riacho S-NKm 25 BR-29197900 Aracruz ES Brazil MTA Ctr Ecol Res Inst Ecol & Bot Alkomany U 2-4 H-2163 Vacratot Hungary Eotvos Lorand Univ Dept Plant Taxon Ecol & Theoret Biol Pazmany P Stny 1-C H-1117 Budapest Hungary

Monitoring and evaluating forest restoration projects is a challenge especially in large-scale, but the remote monitoring of indicators with the use of synoptic, multispectral and multitemporal data allows us to gauge the restoration success with more accurately and in small time. The objective of this study was to elaborate and compare methods of remote monitoring of forest restoration using Light Detection and Ranging (LIDAR) data and multispectral imaging from Unmanned Aerial Vehicle (UAV) camera, in addition to comparing the efficiency of supervised classification algorithms maximum likelihood (ML) and Random Forest (RF). The study was carried out in a restoration area with about 74 ha and five years of implementation, owned by Fibria Celulose S.A., in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, Near Infrared) on UAV and LIDAR data composition (intensity image, Digital Surface Model, Digital Terrain Model, normalized Digital Surface Model). The monitored restoration indicator was the land cover separated in three classes: canopy cover, bare soil and grass cover. The images were classified using the ML and RF algorithms. To evaluate the accuracy of the classifications, the Overall Accuracy (OA) and the Kappa index were used, and the last was compared by Z test. The area occupied by different land cover classes was calculated using ArcGIS and R. The results of OA, Kappa and visual evaluation of the images were excellent in all combinations of the imaging methods and algorithms analyzed. When Kappa values for the two algorithms were compared, RF presented better performance than ML with significant difference, but when sensors (UAV camera and LIDAR) were compared, there were no significant differences. There was little difference between the area occupied by each land cover classes generated by UAV and LIDAR images. The highest cover was generated for canopy cover followed by grass cover and bare soil in all classifie

关键词： Light Detection and Ranging (LIDAR) Unmanned Aerial Vehicle (UAV) Random Forest (RF) maximum likelihood algorithm Recovery of degraded areas Forest restoration

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Fractional Brownian motion: Difference iterative forecasting models

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CHAOS SOLITONS & FRACTALS 2019年 123卷 347-355页

作者： Song, Wanqing Li, Ming Li, Yuanyuan Cattani, Carlo Chi, Chi-Hung Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201620 Peoples R China East China Normal Univ Sch Informat Sci & Technol Shanghai Peoples R China Zhejiang Univ Ocean Coll Hangzhou 316021 Zhejiang Peoples R China Tuscia Univ DEIM Engn Sch Viterbo Italy CSIRO Data 61 Hobart Tas 7015 Australia

Forecasting non-stationary stochastic time series represents a rather complex problem. The reason is that such temporal series are not only self-similar but also exhibit a Long-Range Dependence (LRD). As it is known, the Fractional Brown Motion (FBM) can generate a non-stationary stochastic time series with self-similarity and LRD. In this study we investigate the properties of the LRD for identification of self-similarity and the LRD of non-stationary stochastic series by Hurst exponent. Parameter estimation is proposed for Stochastic differential Equation (SDE) of FBM based on maximum likelihood Estimation (MLE), and proves the convergence of MLE. The SDE is *** difference equation constructed is the prediction model of the iterative format based on FBM. Monte Carlo simulation is applied to check the validity and accuracy of parameter estimation. We also give a practical example to demonstrate the appropriateness of the predictive model. (C) 2019 Published by Elsevier Ltd.

关键词： Fractional Brown motion Long-range dependence Stochastic partial differential equation maximum likelihood algorithm Difference equation

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Harmonic estimation in power systems using an optimised adaptive Kalman filter based on PSO-GA

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第17期13卷 3968-3979页

作者： Xi, Yanhui Tang, Xin Li, Zewen Cui, Yonglin Zhao, Ting Zeng, Xiangjun Guo, Jun Duan, Wei Changsha Univ Sci & Technol State Key Lab Disaster Prevent & Reduct Power Gri Changsha 410114 Hunan Peoples R China Natl Univ Def Technol Coll Syst Engineer Changsha 410073 Hunan Peoples R China

A hybrid particle swarm optimisation (PSO) and genetic algorithm (GA) aided Kalman filter (PSO-GA-KF) method for dynamic harmonic state estimation in the power system is investigated. The initial choice of states and KF's parameters, such as process and measurement error covariance matrices significantly affects the estimation precision. Aiming at this problem, a combination of PSO and GA (PSO-GA) is proposed to optimise KF's parameters. In this hybrid algorithm, by replacing the gene mutation operator of GA, the PS algorithm mutation operator is constructed, which can adjust the evolution direction and range based on historical records and swarm records, leading to avoiding the blindness of GA mutation and reducing the probability of devious mutation and enhancing the velocity of evolution. Thus, the global search ability of the hybrid PSO-GA can ensure KF has more accurate estimation of harmonics. To test the effectiveness of the algorithm, several time-varying signals are simulated with harmonics and decaying DC components in the presence of amplitude drift and white noise. Simulation results show that the proposed hybrid algorithm has more accurate estimation, faster convergence and better robustness against noise in comparison with the conventional Kalman filter (KF), KF based on the maximum likelihood and PSO aided KF (PSO-KF).

关键词： genetic algorithms particle swarm optimisation power system state estimation adaptive Kalman filters power system harmonics harmonic analysis estimation theory probability power harmonic filters genetic algorithm dynamic harmonic state estimation measurement error covariance matrices gene mutation operator PS algorithm mutation operator time-varying power system signals hybrid PSO-GA mutation optimised adaptive Kalman filter parameters PSO-GA-KF parameters probability global search ability maximum likelihood algorithm

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Estimation of the resting motor threshold (RMT) in transcranial magnetic stimulation using relative-frequency and threshold-hunting methods in brain tumor patients

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ACTA NEUROCHIRURGICA 2019年第9期161卷 1845-1851页

作者： Engelhardt, Melina Schneider, Heike Gast, Theresa Picht, Thomas Charite Dept Neurosurg Charitepl 1 D-10117 Berlin Germany Charite Einstein Ctr Neurosci Charitepl 1 D-10117 Berlin Germany Charite Int Grad Program Med Neurosci Charitepl 1 D-10117 Berlin Germany

Background Application of transcranial magnetic stimulation is often based on the resting motor threshold. The aim of this study was to validate recent findings on the advantage of resting motor threshold estimation using adaptive threshold-hunting algorithms over the Rossini-Rothwell method in a clinical sample and healthy subjects. Methods Resting motor thresholds in 115 patients with a brain tumor and 10 healthy subjects were assessed using the Rossini-Rothwell method and compared to an adaptive threshold-hunting algorithm. In healthy subjects, this measurement was repeated twice to capture test-retest reliability of both methods. Efficiency of both methods was assessed by comparing the number of pulses needed for resting motor threshold estimation. Results There was no significant difference between the Rossini-Rothwell method and the adaptive threshold-hunting algorithm in patients and healthy controls with limits of agreement between +/- 12 V/m. There was a strong intraclass correlation and both methods showed a good test-retest reliability. However, the adaptive threshold-hunting algorithm was significantly faster. Conclusions The adaptive threshold-hunting algorithm was more efficient in assessing the resting motor threshold, while reaching comparable results as the Rossini-Rothwell method. Thus, our results support the advantage of adaptive threshold-hunting algorithms to determine the resting motor threshold also in a clinical sample.

关键词： Transcranial magnetic stimulation (TMS) Resting motor threshold (RMT) Rossini-Rothwell method Adaptive threshold-hunting maximum likelihood algorithm

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Exploring 16 years changing dynamics for land use/land cover in Pearl City (Thoothukudi) with spatial technology

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SPATIAL INFORMATION RESEARCH 2017年第4期25卷 547-554页

作者： David, T. Immanuvel Mukesh, M. V. Kumaravel, S. Ramesh, G. Premkumar, R. Annamalai Univ Dept Earth Sci Chidambaram Tamil Nadu India

Land use land cover (LU/LC) changes over the period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. The virtual assessment of LU/LC changes between 2000 and 2016 is carried out in Pearl City (Thoothukudi) using Remote-Sensing data and GIS tool. This change detection is done by 15 m resolution cloud-free Advanced Spaceborne Thermal Emission and Reflection Radiometer data captured during the year 2000 and 2016. The dynamic changes depict the major land use features like settlements, saltpan, crop land, vegetation, barren and water body from satellite data through supervised classifications of a maximum likelihood algorithm. The classified images highlight a series of constructive results in settlement (4.30%), vegetation (4.00%), saltpan (0.24%) and pessimistic results in barren land (-7.68%), crop land (-0.64%) and water body (-0.23%) respectively. The study recommends that urbanization of settlement land usage is highly mobilized in Thoothukudi coastal areas.

关键词： Changing dynamics Land use/land cover (LU/LC) Pearl City maximum likelihood algorithm

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Security and Resolution enhanced Transmission of Medical Image through IDMA aided Coded STTD System 6

Security and Resolution enhanced Transmission of Medical Ima...

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IEEE International Conference on Communication and Signal Processing (ICCSP)

作者： Mithra, K. Vishvaksenan, K. S. Anna Univ SSN Coll Engn Dept ECE Madras Tamil Nadu India

ISBN: (纸本)9781509038008

The transmission of the medical images through a wireless network in a highly secured manner is an important issue in image transmission system. The clarity of medical image is essential as it involves the treatment offered to the patients. Super-resolution is performed using a novel technique called SPARSE based super-resolution. An image with lesser resolution can be enhanced into a high resolution image using this method so that the fine details of the medical image can be viewed clearly. The medical images are more vulnerable to various types of attacks like geometric attacks, stochastic attacks, cryptographic attacks etc, as the transmission takes place through wireless networks. The Arnold Cat-map (ACM) transform algorithm is employed as the encryption algorithm, in order to avoid tampering of the image details. Interleave Division Multiple Access (IDMA) scheme is used as the multiple access technique as it can support more number of users simultaneously. We use Space Time Transmit Diversity (STTD) as the Multi-Input-Multi-Output(MIMO) system for wireless transmission of the image. The simulations show that the performance of STTD system shows good results and the medical image with high resolution is finally obtained in a highly authenticated manner.

关键词： SPARSE representation Dictionary learning maximum likelihood algorithm STTD

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Correlation Dimension Estimation of 2D Fractal Images based on Optimal Scanning Path 6

Correlation Dimension Estimation of 2D Fractal Images based ...

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6th Mediterranean Conference on Embedded Computing (MECO)

作者： Parshin, Alexander Parshin, Yury Ryazan State Radioengn Univ Radio Devices Dept Ryazan Russia

ISBN: (纸本)9781509067428

This paper deals with an investigation of the influence of the pixel ordering on estimation of the correlation dimension. Several scanning paths are considered. The comparison of this paths effectiveness is performed by calculating the dimension. The fractal Brownian surface is accepted as a model of the fractal object image. The estimation of correlation dimension is performed by maximum likelihood method.

关键词： image processing scanning path maximum likelihood algorithm fractal Brownian surface correlation dimension

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Textural processing using maximum likelihood estimation of fractal dimension by independent and dependent samples 17

Textural processing using maximum likelihood estimation of f...

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17th International Radar Symposium (IRS)

作者： Parshin, Alexander Parshin, Yuri Ryazan State Radioengn Univ Radio Devices Dept Ryazan Russia

Paper has described algorithms of the fractal dimension estimation. Their effectiveness is considered in condition of independent and dependent samples of vectors in pseudophase space. Model of the fractal object base... 详细信息

ISBN: (纸本)9781509025183

关键词： maximum likelihood algorithm textural processing fractal object dependent sample radar image

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Analysis of maximum likelihood Estimation of Fractal Dimension by Independent and Dependent Samples 5

Analysis of Maximum Likelihood Estimation of Fractal Dimensi...

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5th Mediterranean Conference on Embedded Computing (MECO)

作者： Parshin, Alexander Parshin, Yuri Ryazan State Radioengn Univ Radio Devices Dept Ryazan Russia

ISBN: (纸本)9781509022212

Paper describes algorithms of the fractal dimension estimation. Their effectiveness is considered in condition of independent and dependent samples of vectors in pseudophase space. Expression for the correlation dimension estimate for dependent samples is calculated. Ways of sample ordering are considered. Appliance of these algorithms for textural processing is proposed.

关键词： maximum likelihood algorithm textural processing fractal object dependent sample radar image

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