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Sparse representation using over-complete dictionaries have shown to produce good quality results in various image processing tasks. Dictionary learning algorithms have made it possible to engineer data adaptive dictionaries which have promising applications in image compression and image enhancement. The most common sparse dictionary learning algorithms use the techniques of matching pursuit and...
The ETSI TC SmartBAN defined system is designed for body area networks supporting both on-body links and links to implanted devices. The system operates at the 2.4 GHz ISM band, where there are also other wireless radio systems, such as Bluetooth and WiFi. The SmartBAN system simulation model has been created to Matlab and the system performance was studied in the IEEE 802.15.6 channel model 3 with...
For more than two decades, the key objective for synthesis of linear decompressors has been maximizing encoding efficiency. For combinational decompressors, encoding satisfiability is dynamically checked for each specified care bit. By contrast, for sequential linear decompressors (e.g. PRPGs), encoding is performed for each test cube; the resultant static encoding considers that a test cube is encodable...
In this paper we compare two recent threads of research on the stabilization of non-linear control systems under information constraints. In a deterministic setting, characterizations of the smallest bit rate of a noiseless channel connecting a state coder to a controller have been obtained, above which local stabilization or set-invariance is possible. These characterizations use quantities similar...
This paper investigates resource allocation algorithms that use limited communication - where the supplier of a resource broadcasts a coordinating signal using one bit of information to users per iteration. Rather than relay anticipated consumption to the supplier, the users locally compute their allocation, while the supplier measures the total resource consumption. Since the users do not compare...
In order to simulate this feature and detect the salient region rapidly, we propose the Spatial-Temporal Feature in Compress Domain (STFCD) model. By respectively using H.264 residual coding length and motion vector coding length, we simulate the salient stimulus intensity and then get video saliency features. Finally, we use the linear weighted fusion algorithm to get the final video saliency maps...
This study investigates the impact of genotypic and behavioral diversity maintenance methods on controller evolution in multi-robot (RoboCup keep-away soccer) tasks. The focus is to examine the impact of these methods on the transfer learning of behaviors, first evolved in a source task before being transferred for further evolution in different but related target tasks. The goal is to ascertain an...
The Sum of Absolute Transformed Differences (SATD) computation is one of the most time consuming functions of the High Efficiency Video Codec (HEVC) reference model (HM). Thus, dedicated hardware architectures are demanded for such metric. In HM, the SATDs are computed using the Hadamard Transform (HT) 8×8 or 4×4. When the partition sizes are larger than those two HT sizes listed, the SATD is computed...
To improve research efficiency of engineering problems, Surrogate model has gained its popularity in replacing real engineering model. This paper proposes a kind of Global Sequential Sampling Algorithm (GSSA) based on surrogate model. With the process of iteration, GSSA can sample both in unexplored region and large-error region, then iteratively update the samples. OLHS is used as initial sampling...
Construction engineering is considered as a complex network system project. By analyzing the relationship of construction costs and reliability in engineering project, a mathematical model is established to optimize the costs and genetic algorithm (GA) is used for this purpose. In the application of GA, penalty function is used to handle the constraint. Ranking based on the evaluation function and...
Genome data increasing exponentially since the last decade, compressing genome with Markov models has been proposed as an effective statistical method. However, existing methods set a static order-k Markov models to compress various genomes. Employing static order-k Markov model could result in a sub-optimal orders on some genomes. In this paper, we propose a compression method that relies on a pre-analysis...
Ensemble methods are considered among the state-of-the-art predictive modeling approaches. Applied to modern big data, these methods often require a large number of sub-learners, where the complexity of each learner typically grows with the size of the dataset. This phenomenon results in an increasing demand for storage space, which may be very costly. This problem mostly manifests in a subscriber...
Smart grid (SG) is an efficient technology for electrical power distribution and management by incorporating two-way communications between utilities and customers. The versatile features of cognitive radio (CR) technology meet the requirements of SG communication and have drawn much attention. In this paper, we study the On-Demand cognitive radio communication for SG. Our contributions includes two...
The inclusion of a previously non-existent traffic class required by the Smart Grid poses many difficulties on OFDMA based wireless communication systems. In this paper, we develop a resource allocation algorithm based on the ecological research Lotka-Volterra equations. Each class of traffic is modelled as a species and they compete over the telecommunications resources. Constraints were then placed...
A novel approach to design capacity-approaching variable-length constrained sequence codes has recently been developed. A critical step in this design process is the construction of minimal sets based on a finite state machine description of the encoders. In this paper we propose three generalized criteria to select the state that will result in construction of the minimal set with the best achievable...
The recursive filter (IIR) parallel programming on SIMD is more difficult than that of nonrecursive algorithms due to data dependency. Several transformation methods for parallel coding of IIR filter on SIMD have already been proposed to deal with data dependency. However, the inherent prologue and epilogue in these methods obviously increase the complexity of control structures and induce extra hardware...
Bus holding is the most used control strategy to improve bus service reliability. This paper presents a coordinated holding control framework based on multi-agent reinforcement-learning (MARL-H) to mitigate bus bunching in real-time on a bus corridor. The MARL-H framework depicts a combination of agents and methods to make decision of coordinated holdings. Coordination Graphs (CGs) are introduced...
Due to their complexity, currently available bounded model checking techniques based on Boolean Satisfiability and Satisfiability Modulo Theories inadequately handle non-linear floating-point and integer arithmetic. Using a numerical approach, we reduce a bounded model checking problem to a constraint satisfaction problem. Currently available techniques attempt to solve the constraint problem but...
Mobile Cloud Storage (MCS) systems – cloud storageon mobile devices without access to remote data center-type cloud resources, are not only interesting from a theoretical point of view, as they pose the most challenging design settings, but also important in enabling real-world applications such as disaster relief, military operation, and mining in remote areas. Central to MCS design is how to minimize...
Machine-to-machine communications (M2M) provide a promising solution for accurately collecting real-time status information of primary equipment in substations. However, the system quality of service (QoS) might be severely degraded by the high-amplitude impulsive noise produced by primary equipment. In this paper, we firstly propose a multi-antenna M2M communications based architecture for substation...
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