Advanced Materials Research Vols. 850-851

Abstract: For stochastic resonance can enhance the signal-to-noise ratio, it is widely applied to detect weak signal in a strong noise background. Aiming at the issue of the traditional stochastic resonance only applicable to deal with small parameters signals, a weak signal detection method based on under sampling stochastic resonance was proposed. Stochastic resonance was successfully expanded into the applications of the large parameters signals on the basis of scale-transformation and retrieve technology in the under sampling stochastic resonance. The improved stochastic resonance model was put forward and simulation results have proved the validity of the method. Large parameters weak signal mixed with strong noise is detected accurately. This method is effective for future application.

Abstract: The higher order maximal orthogonal vector basis functions are used to get targets sampling information in interpolation/extrapolation of electromagnetic responses in time and frequency domain. With the method, the computational complexity of sampling would decrease sharply without loss of accuracy. As a result, the proposed method solved the problem of high computational complexity and great resource consuming of traditional sampling method. Some numerical results are given to verify the high efficiency and accuracy of this method.

Abstract: Conventional compressed sensing is accomplished via random modulation in analog domain. In this paper, a compressed sensing method based-on digital multi-channel sampling is proposed, which is used for signal spectrum detection and evaluation. This compressed sensing method is fulfilled by random modulation in digital domain and aliasing signal spectrum to full frequency range, sampling in Nyquist frequency below followed and digital multi-channels associated signal reconstruction. Examples of experiments show this method is useful and some merits are achieved, such as reduction of hardware complexity, saved memory largely and achieved real-time data transmission.

Abstract: Signals can be sampled in sub-Nyquist rate based on information sampling, which enables sample high bandwidth signal use low frequency. In this paper, a compressed sampling system based on multiphase pre-random filter is studied, in which the filtered signals by periodical random modulation in digital domain, then the spectrum information of original signals is reconstructed from multi-channel signals. The hardware system is designed based in GC5016 and DSP. Simulation and experiment results demonstrated the validity and practicability of signal spectrum detection.

Abstract: With the rapid development of dynamical partial reconfiguration technology, FPGA (Field Programmable Gate Array) is able to allow independent tasks to be executed concurrently without interfering with each other, which increases its flexibility and performance, but on the other hand leads to multi-task scheduling problem. The task scheduling in this paper is the problem of task sequencing, which adjusts the entering sequence of the incoming tasks with the consideration of the attributes of tasks and the utilization of FPGA. A conditional preemption based task sequencing method is proposed that allows tasks that arrive later to be executed in advance as long as the previous tasks can still be guaranteed to enter the FPGA on time. Simulations show that these methods can effectively decrease the waiting ratio of task sets, thus improving the flexibility and utilization of FPGA.

Abstract: Current 2D FPGA allows independent tasks to run concurrently without interfering with each other, which makes it confront task placement problem. Task placement consists of placement management and placement selection. Placement management manages all of the available locations on the FPGA while placement selection selects the proper location for each incoming task from the current available locations. Since we have proposed a Vertex-Scan (VS) algorithm for placement management that can efficiently find all free locations on the FPGA, this paper focuses on the problem of placement selection for tasks. A cost function based placement selection method is proposed that formalizes the influence of both time factor and space factor on the generation of fragmentation in FPGA. Simulations show that compared with the other methods, our method can achieve the lowest ratio of waiting tasks and waiting time. In addition, our methods advantages become more prominent especially in the circumstances of medium or smaller task sizes, and shorter time intervals.

Abstract: In this paper, the spectral residual method is applied in the underwater image data for detecting the animals. The system is designed to assist the underwater monitor system survey operations, specialized to the task of animal detection. Firstly, the regularity for the frequency spectrum of the images collected in the underwater world is discovered by the statistical analysis. Then we transform the input image into the spatial frequency domain and singularities including in the frequency curve is extracted by average filtering. Finally, these singularities are inverse transformed from the frequency domain into spatial domain and the saliency area is detected. Experimental results, which have been performed on a set of real underwater images acquired in different environments, demonstrate the robustness and the accuracy of the proposed system in the task of underwater animal detection.

Abstract: Forward-scattering exists in the process of underwater range-gated imaging. Taking the forward-scattering in the process of illumination and reflection into account, it is obtained the conclusion that when the imaging distance increases, the forward-scattering power decreases; when the attenuation coefficient increases, the forward-scattering power decreases.

Abstract: Optimization of preventive maintenance interval decision for vessel equipment is a multi-attribute decision making problem. But the current studies on the preventive maintenance strategies are mostly with single-objective and based on the assumptions that equipments operating for unlimited time. In this paper, a multi-objective optimization model in limited time is established basing on the existing studies. And the case study of a certain type diesel engine fuel system is used to illustrate the methodology.

Abstract: This paper tries to use Data Envelopment Analysis (DEA) as the foundation, combining Fuzzy Comprehensive Assessment (FCA) method and Analytic Hierarchy Process (AHP), to make decisions for the project. First we use FCA method to analyze and quantize each index, then use AHP method to determine the weight of each index, use Evaluation Model of DEA Cross-efficiency to reduce the error of expert evaluation and weight in the FCA method. This paper will give the detailed steps. Finally, we use a case to test the reliability and feasibility of our method. We think, this paper will provide a now method for the Construction project bidders.