• Title/Summary/Keyword: Robust adaptive algorithm

Search Result 376, Processing Time 0.029 seconds

Software Design of Packet Analyzer based on Byte-Filtered Packet Inspection Mechanism for UW-ASN

  • Muminov, Sardorbek;Yun, Nam-Yeol;Park, Soo-Hyun
    • Journal of Korea Multimedia Society
    • /
    • v.14 no.12
    • /
    • pp.1572-1582
    • /
    • 2011
  • The rapid growth of UnderWater Acoustic Sensor Networks (UW-ASNs) has led researchers to enhance underwater MAC protocols against limitations existing in underwater environment. We propose the customized robust real-time packet inspection mechanism with addressing the problem of the search for the data packet loss and network performance quality analysis in UW-ASNs, and describe our experiences using this approach. The goal of this work is to provide a framework to assess the network real-time performance quality. We propose a customized and adaptive mechanism to detect, monitor and analyze the data packets according to the MAC protocol standards in UW-ASNs. The packet analyzing method and software we propose is easy to implement, maintain, update and enhance. We take input stream as real data packets from sniffer node in capture mode and perform fully analysis. We were interested in developing software and hardware designed tool with the same capabilities which almost all terrestrial network packet sniffers have. Experimental results confirm that the best way to achieve maximum performance requires the most adaptive algorithm. In this paper, we present and offer the proposed packet analyzer, which can be effectively used for implementing underwater MAC protocols.

Digital Image Encryption Method Using Interleaving and Random Shuffling (인터리빙과 랜덤 셔플링을 이용한 디지털 영상의 암호화 방법)

  • Lee Ji-Bum;Ko Hyung-Hwa
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.31 no.5C
    • /
    • pp.497-502
    • /
    • 2006
  • In this paper, we propose a digital image encryption method using adaptive interleaving and multiple random shuffling table to improve the existing encryption methods which use a fixed random shuffling table. In order to withstand the plaintext attack, at first, we propose a interleaving method that is adaptive to the local feature of image. Secondly, using the proposed interleaving only shuffling method and multiple shuffling method that is combined interleaving with existing random shuffling method, we encrypted image by shuffled the DPCM processed 88 blocks. Experimental results show that, the proposed algorithm is very robust to plaintext attack and there is no overhead bit.

A Perceptually-Adaptive High-Capacity Color Image Watermarking System

  • Ghouti, Lahouari
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.11 no.1
    • /
    • pp.570-595
    • /
    • 2017
  • Robust and perceptually-adaptive image watermarking algorithms have mainly targeted gray-scale images either at the modeling or embedding levels despite the widespread availability of color images. Only few of the existing algorithms are specifically designed for color images where color correlation and perception are constructively exploited. In this paper, a new perceptual and high-capacity color image watermarking solution is proposed based on the extension of Tsui et al. algorithm. The CIELab space and the spatio-chromatic Fourier transform (SCFT) are combined along with a perceptual model to hide watermarks in color images where the embedding process reconciles between the conflicting requirements of digital watermarking. The perceptual model, based on an emerging color image model, exploits the non-uniform just-noticeable color difference (NUJNCD) thresholds of the CIELab space. Also, spread-spectrum techniques and semi-random low-density parity check codes (SR-LDPC) are used to boost the watermark robustness and capacity. Unlike, existing color-based models, the data hiding capacity of our scheme relies on a game-theoretic model where upper bounds for watermark embedding are derived. Finally, the proposed watermarking solution outperforms existing color-based watermarking schemes in terms of robustness to standard image/color attacks, hiding capacity and imperceptibility.

Multiple Object Detection and Tracking System robust to various Environment (환경변화에 강인한 다중 객체 탐지 및 추적 시스템)

  • Lee, Wu-Ju;Lee, Bae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.46 no.6
    • /
    • pp.88-94
    • /
    • 2009
  • This paper proposes real time object detection and tracking algorithm that can be applied to security and supervisory system field. A proposed system is devide into object detection phase and object tracking phase. In object detection, we suggest Adaptive background subtraction method and Adaptive block based model which are advanced motion detecting methods to detect exact object motions. In object tracking, we design a multiple vehicle tracking system based on Kalman filtering. As a result of experiment, motion of moving object can be estimated. the result of tracking multipul object was not lost and object was tracked correctly. Also, we obtained improved result from long range detection and tracking.

Clutter Rejection Method using Background Adaptive Threshold Map (배경 적응적 문턱치 맵(Threshold Map)을 이용한 클러터 제거 기법)

  • Kim, Jieun;Yang, Yu Kyung;Lee, Boo Hwan;Kim, Yeon Soo
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.17 no.2
    • /
    • pp.175-181
    • /
    • 2014
  • In this paper, we propose a robust clutter pre-thresholding method using background adaptive Threshold Map for the clutter rejection in the complex coastal environment. The proposed algorithm is composed of the use of Threshold Map's and method of its calculation. Additionally we also suggest an automatic decision method of Thresold Map's update. Experimental results on some sets of real infrared image sequence show that the proposed method could remove clutters effectively without any loss of detection rate for the aim target and reduce processing time dramatically.

Prediction of compressive strength of bacteria incorporated geopolymer concrete by using ANN and MARS

  • X., John Britto;Muthuraj, M.P.
    • Structural Engineering and Mechanics
    • /
    • v.70 no.6
    • /
    • pp.671-681
    • /
    • 2019
  • This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate (Na2SiO3) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature (28C) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

Adaptive On-line State-of-available-power Prediction of Lithium-ion Batteries

  • Fleischer, Christian;Waag, Wladislaw;Bai, Ziou;Sauer, Dirk Uwe
    • Journal of Power Electronics
    • /
    • v.13 no.4
    • /
    • pp.516-527
    • /
    • 2013
  • This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

  • Yao, Wei;Fang, Jiakun;Zhao, Ping;Liu, Shilin;Wen, Jinyu;Wang, Shaorong
    • Journal of Electrical Engineering and Technology
    • /
    • v.8 no.2
    • /
    • pp.252-261
    • /
    • 2013
  • In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.

Position and Attitude Control System Design of Magnetic Suspension and Balance System for Wind Tunnel Test using Iterative Feedback Tuning and L1 Adaptive Control Scheme (IFT와 L1 적응제어기법을 이용한 풍동실험용 자기부상 비접촉식 밸런스의 제어시스템 설계)

  • Lee, Dong-Kyu
    • Journal of Aerospace System Engineering
    • /
    • v.11 no.5
    • /
    • pp.28-35
    • /
    • 2017
  • Magnetic Suspension and Balance System (MSBS) demonstrates the capacity to levitate an experimental model absent any mechanical contact using magnetic forces and moments. It allows precise control of position and attitude of the model, and measures external forces and moments acting on the model. For the purpose of acquisition of reliable experimental results under stable and safe conditions, the performance and robustness of the position and attitude control system of MSBS needs to be improved. To this end, Iterative Feedback Tuning (IFT) and L1 adaptive output feedback algorithm were employed to automatically increase command following performance and to ensure robust operation of MSBS with failure of electric power supply. The applicability was validated using computational simulation.

EXTRACTION OF WATERMARKS BASED ON INDEPENDENT COMPONENT ANALYSIS

  • Thai, Hien-Duy;Zensho Nakao;Yen- Wei Chen
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2003.09a
    • /
    • pp.407-410
    • /
    • 2003
  • We propose a new logo watermark scheme for digital images which embed a watermark by modifying middle-frequency sub-bands of wavelet transform. Independent component analysis (ICA) is introduced to authenticate and copyright protect multimedia products by extracting the watermark. To exploit the Human visual system (HVS) and the robustness, a perceptual model is applied with a stochastic approach based on noise visibility function (NVF) for adaptive watermarking algorithm. Experimental results demonstrated that the watermark is perfectly extracted by ICA technique with excellent invisibility, robust against various image and digital processing operators, and almost all compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal components analysis (PCA) based compression.

  • PDF