In order to improve the position precision of Beidou satellite and INS integrated navigation system in all kinds of condition, a BD/INS passive integrated navigation algorithm model was presented. And a fuzzy logic al...
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In order to improve the position precision of Beidou satellite and INS integrated navigation system in all kinds of condition, a BD/INS passive integrated navigation algorithm model was presented. And a fuzzy logic algorithm is designed and used to improve our navigation algorithm. The fuzzy logic algorithm regulate the noise variance paramiters of Kalman filler by monitor its remain error serial, which makes the navigation althrithm adaptive and improve our algorithm's positioning precision. Finally, we explain in emulation mode that our fuzzy logic adaptive algorithm can improve the positioning precision of integrated system efficiently.
The signal-to-noise ratio of Charge Coupled Devices(CCD) output can be improved by the optimization of control parameters of Correlated Double Sampling (CDS). However, the control parameters of CDS of high-speed CCDar...
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The signal-to-noise ratio of Charge Coupled Devices(CCD) output can be improved by the optimization of control parameters of Correlated Double Sampling (CDS). However, the control parameters of CDS of high-speed CCDare difficult to determine from experiments. An adaptive algorithm was proposed to get a better signal to noise ratio of CCD output. With fixed target and exposure parameters, the CDS control parameters such as the width of reset pulse, the timing of noise sampling and data sampling were tuned. The images on all combination of the CDS control parameters were acquired. The square sum of the Tenengrad function of all pixels on each image was used to evaluate the quality of the image. The combination of three CDS parameters corresponding to the maximum sum was chosen as CDS control parameters, resulting the best signal-to-noise ratio of the CCD out. Finally, the algorithm was implemented in Field-Programmable Gate Array (FPGA) and the experiments results showed that compared with the best image acquired without adaptive algorithm, the parameters of Edge Profile are improved from 507.4 pixels per PH to 763.8 pixels per PH, the parameters of MTF50 improved from 526.5 LW/PH to 937.8 LW/PH. It showed that adaptive algorithm can effectively improve the signal to noise ratio of CCD output.
Nowadays data stream processing is becoming the new hot field of database research. Due to the volume and rapidness of data in stream, conventional techniques of query processing won't be suitable any more. In suc...
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Nowadays data stream processing is becoming the new hot field of database research. Due to the volume and rapidness of data in stream, conventional techniques of query processing won't be suitable any more. In such an environment a query is approximate. Histogram is commonly used to describe the distribution of data. This article presents a new algorithm of maintaining histogram under limited memory and guaranteed error. Experiments show that the algorithm is practical and efficient.
Usually, image zooming is an interpolation of the original image, achieving high quality zooming image as fast as possible. But it is well known that many traditional interpolation methods such as bilinear or bicubic ...
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Usually, image zooming is an interpolation of the original image, achieving high quality zooming image as fast as possible. But it is well known that many traditional interpolation methods such as bilinear or bicubic often suffer from blurring edges or introduce zigzag errors. In this paper, a new adaptive image interpolation method based on edge, introducing rectangular interpolation and quincunx interpolation, putting forward the gradient weight function, motivated by the work of Nira Shezaf et al., is presented. The experimental results show that the new method can improve the quality of zoomed image effectively. At last, an evaluation is presented assess the quality of zoomed image.
Due to the fixed group structure(GOP) doesn't use of the correlation between video frames fully, a new adaptive GOP was proposed. The proposed algorithm estimated the bit rate necessary for successful decoding of ...
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Due to the fixed group structure(GOP) doesn't use of the correlation between video frames fully, a new adaptive GOP was proposed. The proposed algorithm estimated the bit rate necessary for successful decoding of Wyner-Ziv frames, which relied on distribution modeling the statistics of the residual between the side information and the WZ frame. Then, the encoder dynamically selected the image group structure by means of bit rates. The new algorithm can further improve the performance of the entire coding system by exploiting the correlation between video frames. The simulation results showed a significant gain in the average PSNR that can reach 0.4~0.7 dB compared with the fixed-GOP coding, meanwhile maintaining a low encode complexity.
An approach using the adaptive sampling interval for a multi-target tracking system is developed in this paper. Via this technique, the tracking system can scan and grasp the target information more effectively. The k...
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An approach using the adaptive sampling interval for a multi-target tracking system is developed in this paper. Via this technique, the tracking system can scan and grasp the target information more effectively. The key development of this approach is that a data association using the global modeling technique and an adaptive procedure algorithm are design for a multi-target tracking system. A comparison of the difference of the general fixed sampling interval and adaptive sampling interval for a tracking system is made in this paper. According to the simulation results, the adaptive sampling interval algorithm proposed in this paper will enhance radar tracking capability and has more accurate performance.
Based on a series of operations such as detecting candidate target trajectories, the optimal algorithm of maximum likelihood ratio judgment and post-processing, etc., this paper presents a kind of adaptive algorithms ...
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Based on a series of operations such as detecting candidate target trajectories, the optimal algorithm of maximum likelihood ratio judgment and post-processing, etc., this paper presents a kind of adaptive algorithms that can automatically recognize the point targets making straight movement with uniform velocity in the field of view from low SNR image sequence in which CN- and UCN- sequences are all suppressed. The theoretical analyses and optimal algorithms of various kinds of operations are expounded in the paper. The experimental results have proved the correctness of theoretical analyses and the feasibility of the adaptive algorithms. The lowest distinguishable SNR is 0.5, and the optimal algorithms are compatible with infrared- and television image sequences. The quantity of data processing can be also greatly reduced by the optimal algorithms.
For the bottleneck of improving the accuracy of minority class samples within the paradigm of imbalanced datasets, a novel under-sampling method based on the cooperative co-evolutionary mechanism was presented in this...
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For the bottleneck of improving the accuracy of minority class samples within the paradigm of imbalanced datasets, a novel under-sampling method based on the cooperative co-evolutionary mechanism was presented in this paper. During the employment of the method, the majority and the minority samples were divided into two populations, which adopted the cooperative co-evolutionary mechanism, dynamically adaptive crossovers and mutation operators to automatically adjust the evolution process within populations. Simulation results prove that the method enhances the capacity of local search, improves the distribution characteristics of populations and strengthens the capacity of global convergence. Moreover, the method notably improves the accuracy of the minority samples without degrading that of the majority ones. Compared to other classical resampling methods, the method shows good noise immunity with more powerful robustness.
The block-based DCT compression methods often cause blocking artifacts due to low bit rates. In order to not only reduce blocking artifacts, but also preserve edges and textures adequately, a new blocking artifacts re...
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The block-based DCT compression methods often cause blocking artifacts due to low bit rates. In order to not only reduce blocking artifacts, but also preserve edges and textures adequately, a new blocking artifacts reduction algorithm is proposed in this paper. The algorithm introduces the definition of homogeneous blocks and the measurement with an alterable threshold for judging whether a shifted block is homogeneous. For each row (or column) of the homogeneous blocks, an adaptive Sigmoid function is used to replace the step function to reduce blocking artifacts. For the inhomogeneous blocks, Sigma filter is used to smooth the blocks. Simulation results show that the proposed algorithm can outperform the algorithms proposed by Liu (2002) and Luo (2003).
This paper proposed an adaptively stochastic algorithm for solving a log-optimal portfolio problem with risk control. By introducing some slack variables, the original problem with inequality constraints is transforme...
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This paper proposed an adaptively stochastic algorithm for solving a log-optimal portfolio problem with risk control. By introducing some slack variables, the original problem with inequality constraints is transformed into a new one with equality constraints, and the latter problem is further changed into a series of unconstrained stochastic optimization problems after the disposal of equality constraints (involving the risk-constraint) by virtue of the penalty function method. These new problems are then adaptively solved by some stochastic algorithms on Riemannian manifolds. Finally, the algorithm is applied to solve the risk-constrained log-optimal portfolio problem with the real data from the Institute of Shanghai Security. The numerical results are satisfactory.
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