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Search Results: 1 - 10 of 17661 matches for " Chun Tung Chou "
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Extended master equation models for molecular communication networks
Chun Tung Chou
Computer Science , 2012, DOI: 10.1109/TNB.2013.2237785
Abstract: We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise the communication. In order to be able to engineer synthetic molecular communication networks, mathematical models for these networks are required. This paper proposes a new stochastic model for molecular communication networks called reaction-diffusion master equation with exogenous input (RDMEX). The key idea behind RDMEX is to model the transmitters as time series of signalling molecule counts, while diffusion in the medium and chemical reactions at the receivers are modelled as Markov processes using master equation. An advantage of RDMEX is that it can readily be used to model molecular communication networks with multiple transmitters and receivers. For the case where the reaction kinetics at the receivers is linear, we show how RDMEX can be used to determine the mean and covariance of the receiver output signals, and derive closed-form expressions for the mean receiver output signal of the RDMEX model. These closed-form expressions reveal that the output signal of a receiver can be affected by the presence of other receivers. Numerical examples are provided to demonstrate the properties of the model.
A Markovian Approach to the Optimal Demodulation of Diffusion-based Molecular Communication Networks
Chun Tung Chou
Quantitative Biology , 2015, DOI: 10.1109/TCOMM.2015.2469784
Abstract: In a diffusion-based molecular communication network, transmitters and receivers communicate by using signalling molecules (or ligands) in a fluid medium. This paper assumes that the transmitter uses different chemical reactions to generate different emission patterns of signalling molecules to represent different transmission symbols, and the receiver consists of receptors. When the signalling molecules arrive at the receiver, they may react with the receptors to form ligand-receptor complexes. Our goal is to study the demodulation in this setup assuming that the transmitter and receiver are synchronised. We derive an optimal demodulator using the continuous history of the number of complexes at the receiver as the input to the demodulator. We do that by first deriving a communication model which includes the chemical reactions in the transmitter, diffusion in the transmission medium and the ligand-receptor process in the receiver. This model, which takes the form of a continuous-time Markov process, captures the noise in the receiver signal due to the stochastic nature of chemical reactions and diffusion. We then adopt a maximum a posterior framework and use Bayesian filtering to derive the optimal demodulator. We use numerical examples to illustrate the properties of this optimal demodulator.
Impact of receiver reaction mechanisms on the performance of molecular communication networks
Chun Tung Chou
Quantitative Biology , 2013, DOI: 10.1109/TNANO.2015.2393866
Abstract: In a molecular communication network, transmitters and receivers communicate by using signalling molecules. At the receivers, the signalling molecules react, via a chain of chemical reactions, to produce output molecules. The counts of output molecules over time is considered to be the output signal of the receiver. This output signal is used to detect the presence of signalling molecules at the receiver. The output signal is noisy due to the stochastic nature of diffusion and chemical reactions. The aim of this paper is to characterise the properties of the output signals for two types of receivers, which are based on two different types of reaction mechanisms. We derive analytical expressions for the mean, variance and frequency properties of these two types of receivers. These expressions allow us to study the properties of these two types of receivers. In addition, our model allows us to study the effect of the diffusibility of the receiver membrane on the performance of the receivers.
Molecular communication networks with general molecular circuit receivers
Chun Tung Chou
Quantitative Biology , 2013,
Abstract: In a molecular communication network, transmitters may encode information in concentration or frequency of signalling molecules. When the signalling molecules reach the receivers, they react, via a set of chemical reactions or a molecular circuit, to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The aim of this paper is to investigate the impact of different reaction types on the information transmission capacity of molecular communication networks. We realise this aim by using a general molecular circuit model. We derive general expressions of mean receiver output, and signal and noise spectra. We use these expressions to investigate the information transmission capacities of a number of molecular circuits.
A Frame Rate Optimization Framework For Improving Continuity In Video Streaming
Evan Tan,Chun Tung Chou
Computer Science , 2011,
Abstract: This paper aims to reduce the prebuffering requirements, while maintaining continuity, for video streaming. Current approaches do this by making use of adaptive media playout (AMP) to reduce the playout rate. However, this introduces playout distortion to the viewers and increases the viewing latency. We approach this by proposing a frame rate optimization framework that adjusts both the encoder frame generation rate and the decoder playout frame rate. Firstly, we model this problem as the joint adjustment of the encoder frame generation interval and the decoder playout frame interval. This model is used with a discontinuity penalty virtual buffer to track the accumulated difference between the receiving frame interval and the playout frame interval. We then apply Lyapunov optimization to the model to systematically derive a pair of decoupled optimization policies. We show that the occupancy of the discontinuity penalty virtual buffer is correlated to the video discontinuity and that this framework produces a very low playout distortion in addition to a significant reduction in the prebuffering requirements compared to existing approaches. Secondly, we introduced a delay constraint into the framework by using a delay accumulator virtual buffer. Simulation results show that the the delay constrained framework provides a superior tradeoff between the video quality and the delay introduced compared to the existing approach. Finally, we analyzed the impact of delayed feedback between the receiver and the sender on the optimization policies. We show that the delayed feedbacks have a minimal impact on the optimization policies.
Signal Reconstruction from Rechargeable Wireless Sensor Networks using Sparse Random Projections
Rajib Rana,Wen Hu,Chun Tung Chou
Computer Science , 2013,
Abstract: Due to non-homogeneous spread of sunlight, sensing nodes possess non-uniform energy budget in recharge- able Wireless Sensor Networks (WSNs). An energy-aware workload distribution strategy is therefore nec- essary to achieve good data accuracy subject to energy-neutral operation. Recently proposed signal approx- imation strategies assume uniform sampling and fail to ensure energy neutral operation in rechargeable wireless sensor networks. We propose EAST (Energy Aware Sparse approximation Technique), which ap- proximates a signal, by adapting sensor node sampling workload according to solar energy availability. To the best of our knowledge, we are the first to propose sparse approximation to model energy-aware workload distribution in rechargeable WSNs. Experimental results, using data from an outdoor WSN deployment suggest that EAST significantly improves the approximation accuracy offering approximately 50% higher sensor on-time. EAST requires the approximation error to be known beforehand to determine the number of measure- ments. However, it is not always possible to decide the accuracy a-priori. We improve EAST and propose EAST+, which, given only the energy budget of the nodes, computes the optimal number of measurements subject to the energy neutral operation.
Embedding Color Watermarks in Color Images
Tung-Lin Wu,Chun-Hsien Chou
EURASIP Journal on Advances in Signal Processing , 2003, DOI: 10.1155/s1687617203211227
Abstract: Robust watermarking with oblivious detection is essential to practical copyright protection of digital images. Effective exploitation of the characteristics of human visual perception to color stimuli helps to develop the watermarking scheme that fills the requirement. In this paper, an oblivious watermarking scheme that embeds color watermarks in color images is proposed. Through color gamut analysis and quantizer design, color watermarks are embedded by modifying quantization indices of color pixels without resulting in perceivable distortion. Only a small amount of information including the specification of color gamut, quantizer stepsize, and color tables is required to extract the watermark. Experimental results show that the proposed watermarking scheme is computationally simple and quite robust in face of various attacks such as cropping, low-pass filtering, white-noise addition, scaling, and JPEG compression with high compression ratios.
Optimal H2 order-one reduction by solving eigenproblems for polynomial equations
Bernard Hanzon,Jan M. Maciejowski,Chun Tung Chou
Mathematics , 2007,
Abstract: A method is given for solving an optimal H2 approximation problem for SISO linear time-invariant stable systems. The method, based on constructive algebra, guarantees that the global optimum is found; it does not involve any gradient-based search, and hence avoids the usual problems of local minima. We examine mostly the case when the model order is reduced by one, and when the original system has distinct poles. This case exhibits special structure which allows us to provide a complete solution. The problem is converted into linear algebra by exhibiting a finite-dimensional basis for a certain space, and can then be solved by eigenvalue calculations, following the methods developed by Stetter and Moeller. The use of Buchberger's algorithm is avoided by writing the first-order optimality conditions in a special form, from which a Groebner basis is immediately available. Compared with our previous work the method presented here has much smaller time and memory requirements, and can therefore be applied to systems of significantly higher McMillan degree. In addition, some hypotheses which were required in the previous work have been removed. Some examples are included.
Survey on Proxy Caching Technologies for Streaming Media
流媒体代理缓存技术研究

YU Jiang,LIU Wei,WANG Tai,CHOU Chun-Tung,
余江
,刘威,王泰,CHOU Chun-Tung

计算机科学 , 2006,
Abstract: With the widespread uses of the streaming technology over Internet, proxy caching has been introduced to the area of media streaming from that of Web content distribution. Due to some distinct characteristics of streaming media object, novel caching techniques for streaming media are required to replace the traditional Web caching techniques. The critical issues and challenges of proxy caching strategies for streaming media are reviewed in this paper. We survey, classify, and compare the state-of-art various proxy caching solutions for streaming media. Finally, the fu ture research issues in this field are outlined.
A Deterministic Construction of Projection matrix for Adaptive Trajectory Compression
Rajib Rana,Mingrui Yang,Tim Wark,Chun Tung Chou,Wen Hu
Computer Science , 2013,
Abstract: Compressive Sensing, which offers exact reconstruction of sparse signal from a small number of measurements, has tremendous potential for trajectory compression. In order to optimize the compression, trajectory compression algorithms need to adapt compression ratio subject to the compressibility of the trajectory. Intuitively, the trajectory of an object moving in starlight road is more compressible compared to the trajectory of a object moving in winding roads, therefore, higher compression is achievable in the former case compared to the later. We propose an in-situ compression technique underpinning the support vector regression theory, which accurately predicts the compressibility of a trajectory given the mean speed of the object and then apply compressive sensing to adapt the compression to the compressibility of the trajectory. The conventional encoding and decoding process of compressive sensing uses predefined dictionary and measurement (or projection) matrix pairs. However, the selection of an optimal pair is nontrivial and exhaustive, and random selection of a pair does not guarantee the best compression performance. In this paper, we propose a deterministic and data driven construction for the projection matrix which is obtained by applying singular value decomposition to a sparsifying dictionary learned from the dataset. We analyze case studies of pedestrian and animal trajectory datasets including GPS trajectory data from 127 subjects. The experimental results suggest that the proposed adaptive compression algorithm, incorporating the deterministic construction of projection matrix, offers significantly better compression performance compared to the state-of-the-art alternatives.
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