This study proposed a new method about clustering in documents. Clustering is a very powerful data mining technique for topic discovery from documents. In document clustering, it must be more similarity between intra-document and less similarity between intra-document of two clusters. The cosine function measures the similarity of two documents. When the clusters are not well separated, partiti...

The cosine window function with the parameters optimized by Genetic Algorithm (GA) is applied in bistatic planar nearfield scattering measurements so as to effectively improve the measurement precision. With the infinitely long ideal conductor cylinder as the target under test, the bistatic planar near-field scattering measurement technique is studied by the method of computer simulation and so...

Cosine tuning is ubiquitous in the motor system, yet a satisfying explanation of its origin is lacking. Here we argue that cosine tuning minimizes expected errors in force production, which makes it a natural choice for activating muscles and neurons in the final stages of motor processing. Our results are based on the empirically observed scaling of neuromotor noise, whose standard deviation i...

In this work, we propose an image inpainting optimization model whose objective functional is a smoothed l norm of the weighted non-decimated discrete cosine transform (DCT) coefficients of the underlying image. By identifying the objective function of the proposed model as a sum of a differentiable term and a non-differentiable term, we give a basic algorithm inspired by Beck and Teboulle’s re...

Tags are often used to describe user-generated content on the Web. However, the available Web applications are not incrementally dealing with new tag information, which negatively influences their scalability. Since the cosine similarity between tags represented as co-occurrence vectors is an important aspect of these frameworks, we propose two approaches for an incremental computation of cosin...

Face recognition has made extraordinary progress owing to the advancement of deep convolutional neural networks (CNNs). The central task of face recognition, including face verification and identification, involves face feature discrimination. However, the traditional softmax loss of deep CNNs usually lacks the power of discrimination. To address this problem, recently several loss functions su...

Although the spectrum of radially periodic images is often expressed in terms of finite or infinite series of Bessel functions, such expressions do not clearly reveal the exact impulsive structure of the spectrum. An alternative Fourier decomposition of radially periodic images, in terms of circular cosine functions, is presented, and its significant advantages are shown. It is shown that the F...

In this paper, we propose an estimator for the Gerber–Shiu function in a pure-jump Lévy risk model when surplus process is observed at high frequency. The constructed based on Fourier–Cosine series expansion and its consistency property thoroughly studied. Simulation examples reveal that our performs better than Fourier transform method sample size finite.