Abstract. In this article, we report on sixth-order and seventh-order iterative methods for solving nonlinear equations. In particular sixth-order derivative-based and derivative-free iterative families are constructed in such a way that they comprise a wide class of sixth-order methods which were developed in the past years. Weighting functions are introduced to enhance the algorithmic efficie...

Cerebral currents responsible for the extra-cranially recorded magnetoencephalography (MEG) data can be estimated by applying a suitable source model. A popular choice is the distributed minimum-norm estimate (MNE) which minimizes the l2-norm of the estimated current. Under the l2-norm constraint, the current estimate is related to the measurements by a linear inverse operator. However, the MNE...

This study investigated the relative contribution of auditory and visual information to speech perception by looking at the effect of visual and auditory degradation on the weighting given to visual cues for native and non-native speakers. Multiple iterations of /ba/, /da/ and /ga/ by five Australian English and five Mandarin Chinese speakers were presented to Australian English, British Englis...

In this paper, a watermark embedding method, using amplitude modulation technique, based on Gaussian pixel-weighting marks was proposed. The method utilized a technique of weighting marks by averaging the luminance of its own pixel and its neighboring pixels, and used it as an additional scaling factor in the existing watermark embedding methods, The watermark retrieval process was borrowed fro...

In text categorization, term weighting methods assign appropriate weights to the terms to improve the classification performance. In this study, we propose an effective term weighting scheme, i.e. tf.rf , and investigate several widely-used unsupervised and supervised term weighting methods on two popular data collections in combination with SVM and kNN algorithms. From our controlled experimen...

Case-Based Reasoning systems retrieve cases using a similarity function based on the K-NN or some derivatives. These functions are sensitive to irrelevant, interacting or noisy features. Many similarity functions weigh the relevance of features to avoid this problem. This article proposes two weighting methods based on Rough Sets theory: Proportional Rough Sets and Dependence Rough Sets. Both w...

We generalize the Allais common consequence effect by describing three common consequence effect conditions and characterizing their implications for the probability weighting function in rank-dependent expected utility. The three conditions—horizontal, vertical, and diagonal shifts within the probability triangle—are necessary and sufficient for different curvature properties of the probabilit...

This paper examines the realization of acausal weighting patterns with two-point boundary-value descriptor systems (TPBVDSs). We restrict our attention to the subclass of TPBVDSs which are extendible, i.e., whose input-output weighting pattern can be extended outwards indefinitely, and stationary, so that their weighting pattern is shift-invariant. Then, given an infinite acausal shift-invarian...

Traditional text classification methods utilize term frequency (tf) and inverse document frequency (idf) as the main method for information retrieval. Term weighting has been applied to achieve high performance in text classification. Although TFIDF is a popular method, it is not using class information. This paper provides an improved approach for supervised weighting in the TFIDF model. The t...

The convergence of the restarted GMRES method can be significantly improved, for some problems, by using a weighted inner product that changes at each restart. How does this weighting affect convergence, and when is it useful? We show that weighted inner products can help in two distinct ways: when the coefficient matrix has localized eigenvectors, weighting can allow restarted GMRES to focus o...