Principe, "Quantized kernel least mean square algorithm," Neural Networks and Learning Systems, IEEE Transactions on, vol. 23, pp. 22-32, Jan 2012.B. Chen, S. Zhao, P. Zhu, J. C. Principe, Quantized kernel least mean square algo- rithm, IEEE Transactions on Neural Networks and ...
Review of quantized kernel-least-mean-square algorithm Consider the kernel trick [1]. The main idea of the method is to use a suitable nonlinear-mapping φ(·). The input signal vector x(b) is transformed into the RKHS by φ(·), and φ(x(b)) (also denoted as φ(b)) is expresse...
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Thus, an image processing algorithm—depending on the linearity of the grey scale encoding—may be performed in linear space and transposed for non-linear gamma display on a “linear” OLED or other suitable PWM driven display where the gamma may be controlled by the subpixel rendering ...
C. Pr´incipe, "Fixed budget quantized kernel least-mean-square algorithm," Signal Processing, vol. 93, no. 9, pp. 2759-2770, 2013.S. Zhao, B. Chen, P. Zhu, and J. C. Pr´incipe, "Fixed budget quantized kernel least-mean-square algorithm," Signal Process- ing, vol. 93, ...
T. Chi, "A modified quantized kernel least mean square algorithm for prediction of chaotic time series," Digital Signal Processing, vol. 48, pp. 130- 136, 2016.Zheng YF, Wang SY, Feng JC et al (2016) A modified quantized kernel least mean square algorithm for prediction of chaotic time...
Quantized kernel least mean square (QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for input space. It can serve as a powerful tool to perform complex computing for network...
We present a quantization-based kernel least mean square (QKLMS) algorithm with a fixed memory budget. In order to deal with the growing support inherent in online kernel methods, the proposed method utilizes a growing and pruning combined technique and defines a criterion, significance, based on...
In this research, a Hierarchical Fractional quantized kernel least mean square (HFQKLMS) filter was devised for data aggregation in WSN. Moreover, the HFQKLMS technique was devised by combining Kernel Least Mean Square and Hierarchical Fractional Bidirectional Least-Mean-Square (HFBLMS) approach. ...
quantized kernel least mean square(QKLMSnonlinear time seriesIdentifying causal relations among simultaneously acquired signals is an important challenging task in time series analysis. The original definition of Granger causality was based on linear models, its application to nonlinear systems may not be...