H.264/AVC is expected to become an essential component in the delivery of wireless multimedia content. While achieving high compression ratios, this codec is extremely vulnerable to transmission errors. These errors g...
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H.264/AVC is expected to become an essential component in the delivery of wireless multimedia content. While achieving high compression ratios, this codec is extremely vulnerable to transmission errors. These errors generally result in spatio-temporal propagation of distorted macroblocks (MBs) which significantly degrade the perceptual quality of the reconstructed video sequences. This paper presents a scheme for resilient transmission of H.264/AVC streams in noisy environments. The proposed algorithm exploits the redundant information which is inherent in the neighboring MBs and applies a Probabilistic Neural Network (PNN) classifier to detect visually impaired MBs. This algorithm achieves Peak Signal-to-Noise Ratio (PSNR) gains of up to 14.29 dB when compared to the standard decoder. Moreover, this significant gain in quality is achieved with minimal overheads and no additional bandwidth requirement, thus making it suitable for conversational and multicast/broadcast services where feedback-based transport protocols cannot be applied.
Audio watermarking is a method that embeds inaudible information into digital audio data. This paper proposes an audio Watermarking technique for protecting audio copyrights based on Human Psychoacoustic Model (HPM), ...
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Audio watermarking is a method that embeds inaudible information into digital audio data. This paper proposes an audio Watermarking technique for protecting audio copyrights based on Human Psychoacoustic Model (HPM), Discrete Wavelet Transform (DWT), Neural Network (NN) and Error correcting code. Our technique exploits frequency perceptual masking studied in HPM to guarantee that the embedded watermark is inaudible. To assure watermark embedding and extraction, neural network is used to memorize the relationships between a Wavelet central sample and its neighbors. To increase robustness of the scheme, the watermark is refined by the Hamming error correcting code while the encoded mark is embedded as new watermark in the transformed audio signal. Our audio watermarking algorithm is robust to common audio signal manipulations like MP3 compression, noise addition, silence addition, bit per sample conversion, noise reduction, dynamic changes and Notch filtering. Furthermore, it allows blind retrieval of embedded watermark which does not need the original audio and makes the watermark perceptually inaudible.
Dealing with radio frequency (RF) front-end impairments will be one of the major design challenges for next-generation wireless communication systems due to conflicting requirements, such as high data rate, low cost a...
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Dealing with radio frequency (RF) front-end impairments will be one of the major design challenges for next-generation wireless communication systems due to conflicting requirements, such as high data rate, low cost and low power consumption. The use of digital compensation of the imperfections appears a very promising method to meet specifications. Pursuing that path, however, requires thorough understanding of the influence of the RF front-end non-idealities on the received signal and the resulting system performance. To this end, this paper reviews the impact of three important impairments, namely, phase noise, IQ imbalance and nonlinearities, on the performance of next-generation high-rate wireless systems. A specific focus is on the difference between transmitter (TX) and receiver (RX) incurred imperfections. Moreover, a generalized error model to capture to aggregate influence of different impairments is presented.
In this paper a new heuristic for transmission scheduling in sensornetworks is proposed, using a model suggested by Chen et al [3]. The performance and complexity of their algorithms are analyzed and it seems that th...
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ISBN:
(纸本)9781424415014
In this paper a new heuristic for transmission scheduling in sensornetworks is proposed, using a model suggested by Chen et al [3]. The performance and complexity of their algorithms are analyzed and it seems that the procedure for optimal scheduling with global channel state information is computationally too intensive for practical networks, while the heuristic methods used in [3] result in far from optimal network lifetimes. In this paper, a new heuristic is proposed, called the ratio minimisation heuristic, which has near optimal performance while maintaining linear complexity in the number of sensors.
It is important for multi-constrained QoS MAC protocols to study the pertinences of QoS metrics. This paper investigates the pertinence of traffic load, average packet delay and delay jitter based on IEEE 802.15.4 wit...
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ISBN:
(纸本)0769529941
It is important for multi-constrained QoS MAC protocols to study the pertinences of QoS metrics. This paper investigates the pertinence of traffic load, average packet delay and delay jitter based on IEEE 802.15.4 with variable beacon order and superframe order in wireless sensor network by simulation and analysis. The relationship formulation of QoS metrics is proposed. Simulation is performed to validate correctness of these formulations, and shows that analytical results are consistent with simulation results.
In this paper, we briefly introduce the importance of intelligent surveillance sensornetworks. Then we propose a very simple application framework for intelligent surveillance sensornetworks.
ISBN:
(纸本)9780769529943
In this paper, we briefly introduce the importance of intelligent surveillance sensornetworks. Then we propose a very simple application framework for intelligent surveillance sensornetworks.
In this paper, a new efficient fast terminal attractor based backpropagation learning algorithm for feedforward neural networks is proposed, which improves the convergence speed. The effectiveness of the proposed algo...
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ISBN:
(纸本)9781424415014
In this paper, a new efficient fast terminal attractor based backpropagation learning algorithm for feedforward neural networks is proposed, which improves the convergence speed. The effectiveness of the proposed algorithm in improving learning speed is shown by the simulation results including a sensor network example.
We propose and study a class of structured and dynamic information push and pull protocols for wireless sensornetworks. For structured information dissemination, our study focuses on the impact of various information...
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ISBN:
(纸本)9783540730897
We propose and study a class of structured and dynamic information push and pull protocols for wireless sensornetworks. For structured information dissemination, our study focuses on the impact of various information demand characteristics on dissemination along some type of backbone structures. Our exploration of dynamic information push and pull focuses on finding optimal strategies in a distributed manner without prior knowledge of information demand characteristics and/or with heterogeneous query distributions. Our theoretical analysis uses a simple grid structure, but the protocol is applicable to arbitrary network topologies. A distributed traffic information system is used as the context of study and the simulation study uses a microscopic traffic simulator to demonstrate some of the ideas discussed in the paper.
The problem of sensor network localization has been addressed with several localization algorithms. These algorithms can be categorized into centralized schemes which require that computations be performed at base nod...
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ISBN:
(纸本)9781424415014
The problem of sensor network localization has been addressed with several localization algorithms. These algorithms can be categorized into centralized schemes which require that computations be performed at base nodes and distributed schemes which divide the network into sub-networks that localize themselves. In this work, we theoretically compare the transmission capacities of a general centralized algorithm against a distributed localization scheme to investigate the practicality of the schemes. We propose a simple model of the transmission overhead required for transmitting localization information and investigate the effect of the number of node links.
This paper introduces a new trust model and a reputation system for wireless sensornetworks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and...
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ISBN:
(纸本)9781424415014
This paper introduces a new trust model and a reputation system for wireless sensornetworks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and applied to binary events and presents a new Gaussian Reputation System for sensornetworks (GRSSN). We introduce a theoretically sound Bayesian probabilistic approach for mixing second-hand information from neighbouring nodes with directly observed information.
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