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1.
Metamerism phenomenon can be used in illuminant detection to ensure the accuracy of light source. A method based on Long‐, Middle‐, Short‐ wavelength cones(LMS) weighting algorithm to evaluate metamerism degree is proposed. The chromatic relationship between the degree of metamerism mismatch and the light source is studied. Herein, the consistency between the metameric indices (MIs) and CIE1976 L*a*b* color difference ranking is analyzed by SRCC, KRCC, PLCC and RMSE. A statistically sampling method to obtain practical LMS cone fundamentals to evaluate metamerism degree is employed. The analysis results obtained show that the method based on LMS weighting algorithm has good evaluation ability and stability in simulation experiments and statistically sampling experiments, which are in line with visual characteristics of human. Proposed method meets the requirements of selecting metameric pairs used in light source detection. The analysis results have certain guiding significance. 相似文献
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基于课题组自主研发的颗粒物检测系统,根据静电感应的原理获得了大量含有随机噪声的粉尘信号.采用自适应噪声对消的方法对粉尘静电感应信号进行提取,并提出一种新的变步长最小均方误差(least mean square,LMS)自适应算法来修改滤波器系数.引入新的步长因子和误差的非线性关系,使算法具有更好的稳态性能,对新算法的机理和参数进行深入分析,更好地提高了低信噪比下算法的收敛速率并保证了稳态时的性能.将该算法用于粉尘静电感应信号的滤波处理,仿真结果证明该算法能很好地滤除随机噪声. 相似文献
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Normalized least mean square (NLMS) was considered as one of the classical adaptive system identification algorithms. Because most of systems are often modeled as sparse, sparse NLMS algorithm was also applied to improve identification performance by taking the advantage of system sparsity. However, identification performances of NLMS type algorithms cannot achieve high‐identification performance, especially in low signal‐to‐noise ratio regime. It was well known that least mean fourth (LMF) can achieve high‐identification performance by utilizing fourth‐order identification error updating rather than second‐order. However, the main drawback of LMF is its instability and it cannot be applied to adaptive sparse system identifications. In this paper, we propose a stable sparse normalized LMF algorithm to exploit the sparse structure information to improve identification performance. Its stability is shown to be equivalent to sparse NLMS type algorithm. Simulation results show that the proposed normalized LMF algorithm can achieve better identification performance than sparse NLMS one. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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The emergence of Information and Communication Technologies (ICTs) make new tools available for users to manage information and knowledge. These tools are used in different contexts, with varying degrees of success. One of these potential application contexts are teaching and learning processes supported by learning platforms. Learning platforms are a way for institutions to provide teachers and learners with a wide range of educational applications and services. However, students’ learning is not only limited to a specific institution or period of time; instead, learning is a lifelong process and encompasses the use of many different tools. Therefore institutional learning environments should be open in order to enable the export of functionalities and import of information and interaction from outside the institution. In order to do so, this study proposes a service-based framework, which uses interoperability specifications and web services to facilitate opening of the institutional learning systems. Such framework has been tested in educational and technical scenarios with similar results, learning platforms can be open and the exportation of functionalities from them to personal contexts can enrich students learning and increase their participation. 相似文献
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In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). ERP generated due to hand movement is filtered through Adaptive Noise Canceller (ANC) from the EEG signals. ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. Performance of the algorithms is evaluated in terms of Signal-to-Noise Ratio (SNR) in dB, correlation between resultant and template ERP, and mean value difference. Testing of their noise attenuation capability is done on contaminated ERP with white noise at different SNR levels. A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment. 相似文献
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This study deals with the asymptotic performance of a multiple-spur cancellation scheme. Radio frequency transceivers are now multi-standard and specific impairment can occur. The clock harmonics, called spurs, can leak into the signal band of the reception stage, and thus degrade the performance. The performance of a fully digital approach is presented here. A one-spur cancellation scheme is first described, for which we exploit the a priori knowledge of the spur frequency to create a reference of the polluting tone with the same frequency. A least-mean-square (LMS) algorithm block that uses this reference to mitigate the polluter is designed. However, due to imperfections in the physical components, there is a shift between the a priori frequency and the actual frequency of the spur, and the spur is affected by Brownian phase noise. Under these circumstances, we study the asymptotic and transient performance of the algorithm. We next improve the transient performance by adding a previously proposed adaptive-step-size process. In a second part of this paper, we present a multiple-spur parallel approach that is based on the one-spur cancellation scheme, for which we provide a closed-form expression of the asymptotic signal-plus-noise interference ratio in the presence of frequency shifts and phase noise. 相似文献
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Adaptive parallel interference cancellation for CDMA systems—A weight selection and filtering scheme
Parallel interference cancellation (PIC) is a well-known multiuser detection algorithm in direct-sequence code-division multiple-access (DS-CDMA) systems. It is typically implemented with a multi-stage architecture. One problem associated with the PIC is that unreliable interference cancellation may occur in the early stages and the system performance may be degraded. Thus, the partial PIC detector was developed to control the cancellation level by use of interference cancellation factors. Partial PIC can be implemented with an adaptive form, in which optimal weights are derived using the least mean square (LMS) algorithm. In this paper, we propose an algorithm improving the conventional adaptive partial PIC. The main idea is to reduce the number of active weights in the LMS algorithm, and to perform weight post-filtering such that the resultant excess mean square error can be reduced. We also analyze the performance of the proposed algorithm and derive the bit error rate of the second stage output. Simulation results verify that the proposed algorithm outperforms the conventional partial PIC, and derived analytical results are accurate. 相似文献