Loading...
Search for:
data-compression
0.007 seconds
Total 38 records
Energy Aware Data Compression in WSN by Signal Processing
, M.Sc. Thesis Sharif University of Technology ; Manzuri Shalmani, Mohammad Taghi (Supervisor)
Abstract
Wireless sensor networks (WSNs) consume energy for their sensing, computation, and communication. To extend the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging their batteries is impossible in most applications. Therefore, energy consumption needs to be monitored and be limited to extend the high performance operation of the network. In this network, the communication module consumes the highest amount of energy. While several methods are proposed to reduce the energy consumption, data compression is one of the most effective ways for energy management by reducing the number of bits to be broadcast. To determine the energy efficiency of the...
An Effective Data Aggregation Mechanism in Wireless Sensor Networks
, M.Sc. Thesis Sharif University of Technology ; Jahangir, Amir Hossein (Supervisor)
Abstract
Wireless sensor networks (WSNs) are tiny devices with limited computation and power supply. For such devices, data transmission is a very energy-consuming operation. Data aggregation eliminates redundancy and minimizes the number of transmissions in order to save energy. This research explores the efficiency of data aggregation by focusing on different aspects of the problem such as energy efficiency, latency and accuracy. To achieve this goal, we first investigate data aggregation efficiency with constraint on delay, which can be compatible with other important system properties such as energy consumption and accuracy. By simulation, we will show that, depending on the application, we can...
Improvement of Level Crossing Sampling’s Performance in Sample Reconstruction, Data Compression and Sampler Stages
, M.Sc. Thesis Sharif University of Technology ; Marvasti, Farokh (Supervisor)
Abstract
Level crossing sampling is a sampling method in which a sample is taken whenever signal crosses predefined and specific levels. In this dissertation, some recommendations are made in order to increase the sampler’s performance in the sampling, data compression, and reconstruction stages.The IMATMirror algorithm is introduced in the sample reconstruction stage. This algorithm is derived from the IMAT reconstruction method. However, additional data processing is done in each iteration, causing the reconstructed signal to satisfy some properties of the Level-Crossing samples.In order to solve the problem of level crossing sampling of extremely bursty signals (ECG signals for example), a sampler...
Analysis of Universal Coding Algorithms for Some Special Classes of Information Sources
, M.Sc. Thesis Sharif University of Technology ; Aref, Mohammad Reza (Supervisor) ; Behroozi, Hamid (Supervisor)
Abstract
The coding and compression of information sources with special probability distribution is the center of concentration of researchers in this field in the last decades. In this dissertation, after a concise introduction to source coding, we focus on the universal source coding and data compression from an algorithmic and information theoretic point of view. First we introduce the fundamental concepts of source coding and data compression. Then, we analysis some algorithms on integer coding and verify their universality and asymptotically optimality. Usually statistics of information sources is not available in communication systems and storage devices, so that applying universal source...
Quantum achievability proof via collision relative entropy
, Article IEEE Transactions on Information Theory ; Vol. 60, issue. 12 , 2014 , pp. 7980-7986 ; ISSN: 00189448 ; Gohari, A
Abstract
In this paper, we provide a simple framework for deriving one-shot achievable bounds for some problems in quantum information theory. Our framework is based on the joint convexity of the exponential of the collision relative entropy and is a (partial) quantum generalization of the technique of Yassaee et al. from classical information theory. Based on this framework, we derive one-shot achievable bounds for the problems of communication over classical-quantum channels, quantum hypothesis testing, and classical data compression with quantum side information. We argue that our one-shot achievable bounds are strong enough to give the asymptotic achievable rates of these problems even up to the...
Performance improvement of spread spectrum additive data hiding over codec-distorted voice channels
, Article European Signal Processing Conference ; Volume. 97, Issue. 9 , 2014 , pp. 2510-2514 ; ISSN: 22195491 ; Kazemi, R ; Behnia, F ; Akhaee, M. A ; Sharif University of Technology
Abstract
This paper considers the problem of covert communication through dedicated voice channels by embedding secure data in the cover speech signal utilizing spread spectrum additive data hiding. The cover speech signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice non-stationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape...
Data compression technique for high resolution wireless photoplethysmograph recording system
, Article International Conference on Space Science and Communication, IconSpace ; 2013 , Pages 345-349 ; 21654301 (ISSN) ; 9781467352314 (ISBN) ; Zahedi, E ; Gan, K. B ; Mohd. Ali, M. A ; Sharif University of Technology
2013
Abstract
Multi-site photoplethysmography is an optoelectronic technique that measures changes in blood volume associated with cardiac contraction. Photoplethysmogram (PPG) recording enables researchers to study the vascular and hemodynamic properties of human subjects. Currently, there is no commercial system available in the market to perform multi-channel PPG recording. The measurements can be obtained from fingertips, ear lobes and toes due to their low absorption and high degree of vasculature. The main objective of this project is to develop a suitable data compression algorithm for two-channel simultaneous high resolution wireless PPG recording system. MATLAB software was used during the...
Test data compression strategy while using hybrid-BIST methodology
, Article Proceedings of IEEE East-West Design and Test Symposium, EWDTS 2013, Rostov-on-Don ; Sept , 2013 ; 9781479920969 (ISBN) ; Tabandeh, M ; Haghbayan, M. H ; Sharif University of Technology
2013
Abstract
In this paper a strategy is proposed for compressing the test data while using concurrent hybrid-BIST methodologyfor testing SoCs. In the proposed method, in addition tousing BIST strategy for testing cores with deterministic sequential test patterns in an SoC( Without using scan chains), (ATE) is used for testing cores with deterministic test patterns through Test Access Mechanism (TAM) or functional bus. As will be shown in experimental results, this process compresses hybrid-BIST overall test patterns considerably that affects the overall Test Application Time (TAT) in comparison with pure deterministic, pure pseudo random, and combination of deterministic and pseudo random test patterns
Energy consumption text and image data compression in WSNs
, Article Lecture Notes in Electrical Engineering ; Volume 152 LNEE , December , 2013 , Pages 683-695 ; 18761100 (ISSN) ; 9781461435341 (ISBN) ; Manzuri, M. T ; Sharif University of Technology
2013
Abstract
Wireless sensor networks (WSNs) consume energy for their sensing, computation, and communication. To extend the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is impossible in most applications. Therefore, energy consumption needs to be monitored and limited to extend the high performance operation of the network. In this network, the communication module consumes the highest amount of energy. This paper demonstrates that among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. To determine the energy efficiency of...
Energy aware data compression in WSN
, Article Lecture Notes in Electrical Engineering ; Volume 152 , 2013 , Pages 673-682 ; 18761100 (ISSN) ; 9781461435341 (ISBN) ; Manzuri, M. T ; Sharif University of Technology
2013
Abstract
Wireless sensor networks (WSNs) use energy for their sensing, computation, and communication. To increase the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is not possible in most applications. Therefore, energy consumption needs to be monitored and limited to increase the energy consumption performance of the network. The communication module uses the highest amount of energy in a WSN. Among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. This paper illustrates an energy consumption reduction in WSN by...
Low-rank matrix approximation using point-wise operators
, Article IEEE Transactions on Information Theory ; Volume 58, Issue 1 , September , 2012 , Pages 302-310 ; 00189448 (ISSN) ; Karbasi, A ; Marvasti, F ; Sharif University of Technology
Abstract
The problem of extracting low-dimensional structure from high-dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace, then simple algorithms using linear projections can find the subspace and consequently estimate its dimensionality. However, if the data lies on a low-dimensional but nonlinear space (e.g., manifolds), then its structure may be highly nonlinear and, hence, linear methods are doomed to fail. In this paper, we introduce a new technique for dimensionality reduction based on point-wise operators. More precisely, let $ {bf A} n...
Range sidelobe reduction filter design for binary coded pulse compression system
, Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 48, Issue 1 , Jan , 2012 , Pages 348-359 ; 00189251 (ISSN) ; Bastani, M. H ; Sharif University of Technology
2012
Abstract
Pulse compression is an active research topic in radar systems. A problem in pulse compression is masking of small targets by the range sidelobes of large nearby targets. A new filter structure is introduced here to suppress the sidelobes of radar signals that result from standard matched filtering. The proposed filter is applicable for any type of binary coding signals. Several techniques are used to calculate the filter coefficients such as Wiener filter technique, Lagrange multiplier method, and linear programming (LP) algorithm. Also, a weighting function is utilized to shape the sidelobe energy in an iterative manner that will yield more sidelobe reduction. Comparison of the proposed...
A content-based digital image watermarking algorithm robust against JPEG compression
, Article IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011, 14 December 2011 through 17 December 2011 ; Dec , 2011 , Pages 432-437 ; 9781467307529 (ISBN) ; Siahkoohi, A ; Shamsollahi, M. B ; Sharif University of Technology
Abstract
Watermarking (imperceptible insertion of data into the host image or soundtracks) has attracted many research interests in the recent decade. The aim of this correspondence is to introduce a none-blind, content-based method for image watermarking. It employs properties of Human Visual System (HVS) and is capable of embedding a high-energy watermark (consequently robust against lossy compressions and other kinds of attacks) while prevents perceptible degradation in the host image. To modulate the binary coded watermark on a spread-spectrum noise, the introduced algorithm is followed by spread-spectrum watermarking. The algorithm was simulated and experimental results represent magnificent...
Joint compressive single target detection and parameter estimation in radar without signal reconstruction
, Article IET Radar, Sonar and Navigation ; Volume 9, Issue 8 , September , 2015 , Pages 948-955 ; 17518784 (ISSN) ; Babaie Zadeh, M ; Sharif University of Technology
Institution of Engineering and Technology
2015
Abstract
In this study, a detector/estimator is proposed for compressed sensing radars, which does not need to reconstruct the radar signal, and which works directly from compressive measurements. More precisely, through direct processing of the measurements, and without the need for reconstructing the original radar signal, the system performs target detection, and then estimates range, Doppler frequency shift and radar cross section in the presence of a Gaussian clutter. It can be seen that for large compression ratios, the detection performance and estimation quality is comparable with a common radar system while having a much lower data rate and with less computational load
Generalised secure distributed source coding with side information
, Article IET Communications ; Volume 4, Issue 18 , 2010 , Pages 2262-2272 ; 17518628 (ISSN) ; Salmasizadeh, M ; Aref, M. R ; Sharif University of Technology
2010
Abstract
New inner and outer bounds on the achievable compression-equivocation rate region for generalised secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and Charlie intend to transmit information to Bob via channels with limited capacity so that he can reliably reconstruct their observations. The eavesdropper, Eve, has access to one of the channels at each instant and is interested in the source of the same channel at the time. Bob and Eve also have their own observations, which are correlated with Alice's and Charlie's observations. In this model, two equivocation and compression rates are defined with respect to the sources...
A fast and adaptive boundary matching algorithm for video error concealment
, Article 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010, Gold Coast, QLD, 13 December 2010 through 15 December 2010 ; 2010 ; 9781424479078 (ISBN) ; Mohammadiha, N ; Kasaei, S ; Sharif University of Technology
2010
Abstract
Low-complexity error concealment techniques for missing macroblock (MB) recovery based on the boundary matching principle are extensively studied and evaluated. In this paper, an improved boundary matching algorithm (BMA) using adaptive search is presented to conceal channel errors in inter-frames of video images. The proposed scheme adaptively selects proper candidate regions to conceal the artifact of a lost block. The candidate regions are examined based on analyzing motion activity of the neighboring MBs. Simulations show that the proposed scheme outperforms both on PSNR and visual quality obviously of about 1-4dB compared to existing methods
An effective data aggregation mechanism for wireless sensor networks
, Article 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, 23 September 2010 through 25 September 2010 ; September , 2010 ; 9781424437092 (ISBN) ; Sharif University of Technology
2010
Abstract
Wireless sensor networks are tiny devices with limited computation and energy capacities. For such devices, data transmission is a very energy-consuming operation. It thus becomes essential to increase the lifetime of a WSN by minimizing the number of bits sent by each device. One well known approach is to aggregate sensor data. Data aggregation is used to eliminate redundancy and minimize the number of transmissions in order to save energy. Most energy efficient aggregation protocols have focused on cluster-based structure approaches. In this paper, we investigate the efficiency of data aggregation by focusing on two aspects of the problem: first how to improve cluster-based routing...
A gaussian process regression framework for spatial error concealment with adaptive kernels
, Article Proceedings - International Conference on Pattern Recognition, 23 August 2010 through 26 August 2010, Istanbul ; 2010 , Pages 4541-4544 ; 10514651 (ISSN) ; 9780769541099 (ISBN) ; Rabiee, H. R ; Pourdamghani, N ; Rohban, M. H ; Sharif University of Technology
2010
Abstract
We have developed a Gaussian Process Regression method with adaptive kernels for concealment of the missing macro-blocks of block-based video compression schemes in a packet video system. Despite promising results, the proposed algorithm introduces a solid framework for further improvements. In this paper, the problem of estimating lost macro-blocks will be solved by estimating the proper covariance function of the Gaussian process defined over a region around the missing macro-blocks (i.e. its kernel function). In order to preserve block edges, the kernel is constructed adaptively by using the local edge related information. Moreover, we can achieve more improvements by local estimation of...
A new approach for distributed image coding in wireless sensor networks
, Article Proceedings - IEEE Symposium on Computers and Communications, 22 June 2010 through 25 June 2010, Riccione ; June , 2010 , Pages 563-566 ; 15301346 (ISSN) ; 9781424477555 (ISBN) ; Zokaei, S ; Rabiee, H. R ; Sharif University of Technology
2010
Abstract
Power and bandwidth constraints are two major challenges in wireless sensor networks. Since a considerable amount of energy in sensor networks is consumed for data transmission, compression techniques may prolong the life of such networks. Moreover, with fewer bits to transmit, the network can cope better with the problem of inadequate bandwidth. In this paper, we consider an image sensor network and propose a paradigm based on the principles of Distributed Source Coding (DSC) for efficient compression. Our method relies on high correlation between the sensor nodes. The algorithm consists of two phases: the Training Phase and the Main Phase. In the Training Phase an aggregation node or a...
MFLP: a low power encoding for on chip networks
, Article Design Automation for Embedded Systems ; Volume 20, Issue 3 , 2016 , Pages 191-210 ; 09295585 (ISSN) ; Taassori, M ; Uysal, S ; Sharif University of Technology
Springer New York LLC
2016
Abstract
Network on chip (NoC) has been proposed as an appropriate solution for today’s on-chip communication challenges. Power dissipation has become a key factor in the NoCs because of their shrinking sizes. In this paper, we propose a new encoding approach aimed at power reduction by decreasing the number of switching activities on the buses. This approach assigns the symbols to data word in such a way that the more frequent words are sent by less power consumption. This algorithm dedicates the symbols with less ones to high probability data and uses transition signaling to transmit data. The proposed method, unlike the existing low power encoding, does not rely on spatial redundancy and keeps the...