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Traffic flow prediction plays an important role in urban traffic management and control. Traditional prediction methods are mostly difficult to meet the high complexity, randomness and uncertainty characteristics of urban traffic flow. In this paper, a new prediction model is proposed based on self-adaptive neural network. Compared with other methods, it possesses the advantages of low computational...
Adaptive HF OFDM system can improve the transmission performance by bit and power loading based on the characteristic of subchannel. Greedy algorithm is the optimal method for finite granularity bit allocation, but it has high computational complexity. A new improved bit and power loading algorithm is proposed for HF OFDM systems in this paper, some bits is pre-allocated to some subchannels based...
The computational complexity of H.264 video coding standard is two or three times higher than that of H.263 and MPEG-4. Especially, the operations of the entropy coding and deblocking filter are the most complex parts in the decoder. In order to reduce the computational complexity of these operations, we propose a fast algorithm for H.264 decoder implementation, which containing a group-based CAVLC...
To find MST (Minimum Spanning Trees) in complete graph is a classical problem in operation research having network design as an important application. It is possible to solve MST problem efficiently, but its Biobjective versions are NP hard. In this paper, we present a comparison of two encoding schemes for representing tree in Biobjective optimization scenario. The three different instances of Biobjective...
Complexity metrics takes an important role to predict fault density and failure rate in the software deployment. Information flow represents the flow of data in collective procedures in the processes of a concrete system. The present static analysis of source code and the ability of metrics are incompetent to predict the actual amount of information flow complexity in the modules. In this paper, we...
Knapsack problem is a typical computer algorithm of NP complete (Nondeterministic Polynomial Completeness) problem. The research of solving this problem has great significance not only in theory, but also in application, for example, resource management, investment decisions and so on. For solving this problem, scholars have developed a number of algorithms, however, they are all have some drawbacks...
This paper proposes a stereoscopic vision algorithm to calculate the disparity map using One-Bit transform (1BT). There are two advantages of the proposed algorithm over the conventional stereoscopic vision algorithms. First, the use of the 1BT reduces the computational complexity of the disparity map calculation. Second, for implementation in private spaces such as homes and communities, the use...
In this paper we present a new algorithm that extends Seitz and Dyer's voxel coloring algorithm. This paper explores a method of voxel coloring which scans only the voxels on the surface of 3D reconstructed scene and the voxels of the nearest neighbors of the 3d reconstructed scene. This method reduces significantly the number of voxels to be processed and retaining the accuracy of actual voxel coloring...
The automatic generation of malicious behavior pattern based on system call trace is important to malware detection. This paper studied the existing generation method of malicious behavior specification. In order to reduce the complexity of pattern generation, it constructs graph which vertex label is unique, and uses these graphs to mine the pattern. To address the issue of limitation of the minimal...
When a stream application that demands real-time processing over continuous data streams is running on a network-on-chip (NoC)-based multiprocessor system-on-chip (MPSoC), two types of deadlocks may occur: (i) the routing-dependent deadlocks, and (ii) the message-dependent deadlocks. In this paper, we focus on the request-request type message-dependent deadlocks, the most devastating deadlocks in...
Compressed sensing theory is a newly developed theory which unites the signal sampling and compression, based on the sparsity characteristic of signal. The union can reduce sampling rate, and then reduce computational complexity of the system without the loss of the performance of the system. The paper describes the theoretical frame and some key technical, and then illustrates the application of...
The throughout of wireless communication systems can be improved by adding multiple antennas at the transmitter and receiver to create multiple-input multiple-output channels. To avoid the prohibitive complexity involved in the ML detectors, some special detectors were proposed to improve the performance-complexity trade-off, such as zero-forcing (ZF), minimum mean-square (MMSE), vertical Bell labs...
Reducing the power consumption while maintaining the response time constraint has been an important goal in server system design. One of the techniques widely explored in the literature to achieve this goal is Dynamic Voltage Scaling (DVS). However, DVS is not efficient in modern systems where the overall power consumption includes a large portion of static power consumption. In this paper, we aim...
Current distributed systems are usually composed of several distributed components that communicate through specific ports. When testing these systems we separately observe sequences of inputs and outputs at each port rather than a global sequence and potentially cannot reconstruct the global sequence that occurred. In this paper we concentrate on the problem of formally testing systems with distributed...
Through the research of current digital signal processing, this paper presents a design with FPGA to achieve FFT, gives the overall implementation framework, and focuses on the design and implementation of the FFT algorithm processing unit, thereby increasing the operation speed of the digital signal processor and reducing the computational complexity.
Sparse signal approximations have become a new tool in signal processing with wide ranging applications from source separation to signal acquisition. Recently, many algorithms for sparse signal reconstruction have been developed, however, greedy algorithms, such as Orthogonal Matching Pursuit algorithm, can have better performance than the other algorithms. Approximate orthogonal matching pursuit...
In this paper, we consider the gene-loss problem which is to infer a species supertree from a collection of gene trees. These gene trees are confounded by complex histories of gene loss and gene duplication events. This problem has been proved to be NP-complete by B. Ma et al. Existing heuristics aimed at solving the gene-loss problem search the space of all possible supertrees guided by a series...
In the paper, we propose a new d-hop Clustering method for a clustering-based multi-hop routing scheme in large-scale wireless sensor network. d-hop clustering means that each cluster contains all nodes that are at distance at most d-hops from the clusterhead, so that the number of clusters can be getting smaller to make it possible to guarantee the combined system performances including end-to-end...
A near-optimal signal detection algorithm with complexity of O(K log K) is proposed for K -input, K -output linear Gaussian vector channels. The proposed algorithm is based on the searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. It is proved that the algorithm can reach the optimal detection result in the case that all cross-correlation values...
Nowadays practical solutions of engineering problems involve model-integrated computing. Model based approaches offer a very challenging way to integrate a priori knowledge into the procedure. Due to their flexibility, robustness, and easy interpretability, the application of soft computing based models, may have an exceptional role. Nevertheless, ever so advantageous their usage can be, it can still...
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