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Accurate performance evaluation for network algorithms is vital to meet various requirements of different applications, such as QoS, network security, traffic engineering. Although worst-case and average-case analysis are widely used in algorithm evaluation, they are often insufficient due to the lack of practicality. Smoothed Analysis (SA) introduces a new concept of smoothed complexity, remedying...
This paper presents a fast-convergence and robust adaptive step size equalization approach for a 14-bit 200MS/s hybrid pipeline-SAR analog-to-digital converters (ADC). The proposed calibration approach corrects errors not only from capacitor mismatch, gain error, op amp nonlinearity, and comparator offset, but also the reference DAC error and inter-stage mismatch errors. It is robust and permits higher...
In order to improve the training efficiency to the data set, an improved adaptive Support Vector Machine (SVM) algorithm with combinational Fuzzy C-means Clustering is proposed. With multi-layer fuzzy C-means clustering algorithm original data are pretreated to remove the training data, which has no contribution to the classification. The remaining data are used to complete the training work for SVM...
The paper is about how to evaluate the intelligent knowledge. We think that the criteria is not only distinguishing ability and accuracy of the algorithm, but also algorithm robustness, stability and so on. Besides positive characters listed above, a fair evaluation system of intelligent knowledge should also include negative characters, such as storage space, running time, training and testing time...
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