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Sparse representation based classification (SRC) as an efficient method has high recognition rate in many pattern recognition applications. Unfortunately, the original SRC method generally requires rigid alignment in classification. In this paper, the feature-based SRC method is addressed by using the PCA-SIFT and SPP-SIFT descriptors, respectively. The presented methods are not only efficient for...
We present a three-step method to predict Prostate cancer (PCa) regions on biopsy tissue samples based on high confidence, low resolution PCa regions marked by a pathologist. First, we apply a texture analysis technique on a high magnification optical image to predict PCa regions on an adjacent tissue slice. Second, we design a prediction model for the same purpose using matrix-assisted laser desorption/ionization...
In the embedded distribution control system, the analogue quantity under test is usually non-linear. In this paper, the concept of variable threshold neuron for the detecting of non-linear analogue is adopted. The subsection linearization and subsection variable slope are chosen as its training methods. It is shown by analyzing and comparing for the two training methods that the subsection linearization...
For the classification problems based on support vector machine, if the sample contains irrelative or even completely irrelative features to the problem, the difference related to the degree of features to the problem becomes such large that may greatly affect the classification effect by means of support vector machine. To solve this problem, a new classification algorithm using SVM based on weighted...
The highly efficient and accurate oil security pre-warning is of important significance for China, a big consumption nation, to establish the scientific safeguarding countermeasures. The SVM approach was employed herein to make empirical analysis on the oil security based on the optimal selection of oil security pre-warning indices. The results show that the oil security will be under the exposure...
Pseudo Chaotic Time Hoping (PCTH) is a recently proposed modulation scheme for UWB impulse radio. Unlike a typical TH-UWB, the PCTH-UWB system exploits concepts from symbolic dynamics to generate aperiodic sequences which modulate the position of pulses. The use of aperiodic TH sequence can enhance the spread-spectrum characteristics of UWB system by removing the spectral feature of the transmitted...
The paper puts forward a variable threshold value artificial neuron structure. The neural function between the output and input can be accurately trained by increasing the density of threshold value. Combined with characteristic of distributed control systems, a long-distance intelligent marking method is proposed and is applied to carry out the process of training threshold value and weight coefficient...
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