Spirals

The authors propose a general fuzzy classification scheme with learning ability using an adaptive network. System parameters, such as the membership functions defined for each feature and the parameterized t-norms used to combine conjunctive conditions, are calibrated with backpropagation. To explain this approach, the concept of adaptive networks is introduced and a supervised learning procedure based on a gradient descent algorithm is derived to update the parameters in an adaptive network. The proposed architecture is applied to two problems: two-spiral classification and Iris categorization. From the experimental results, it is concluded that the adaptively adjusted classifier performs well on an Iris classification problem. The results are discussed from the viewpoint of feature selection

There has recently been widespread interest in the use of multiple models for classification and regression in the statistics and neural networks communities. The hierarchical mixture of experts (HME) has been successful in a number of regression problems, yielding significantly faster training through the use of the expectation maximisation algorithm. In this paper we extend the HME to classification and results are reported for three common classification benchmark tests: exclusive-OR, N-input parity and two spirals

In this letter, it is shown that using magneto-dielectric materials as substrate can increase the in-phase reflection bandwidth of electromagnetic bandgap (EBG) structures. To show this, a compact wideband EBG structure is designed and simulated. The numerical results show that this EBG has an in-phase reflection bandwidth of 70% which is several times greater than a conventional EBG resonating at

A neural network architecture is outlined that self-organizes invariant pattern recognition codes of noisy images. The processing stages are figure-ground separation, boundary segmentation, invariant filtering, and self-organization of a pattern recognition code by an ART 2 network. The article describes a new circuit for boundary segmentation, called the CORT-X filter, that detects, regularizes, and completes sharp (even one-pixel wide) image boundaries in up to 50% noise, while simultaneously suppressing the noise. The CORT-X filter achieves this competence by using nonlinear interactions between multiple spatial scales to resolve a design trade-off that exists between the properties of boundary localization, boundary completion, and noise suppression. The processing levels of the CORT-X filter are analogous to those of the Grossberg-Mingolla Boundary Contour System, but contain only feedforward operations that are easier to implement in hardware. The network nodes in these levels are analogous to cortical simple cells, complex cells, hypercomplex cells, and unoriented and oriented cooperative cells.

This paper presents high-Q and high-inductance-density on-chip inductors fabricated on high-resistivity substrate (HRS) using a 0.12 /spl mu/m SOI CMOS technology with 8 copper metal layers. A peak Q of 52 is obtained at 5 GHz for a 0.6 nH STP (Single-turn, multiple metal levels in Parallel) inductor. An inductance density of 5302 fH//spl mu/m/sup 2/ is obtained for a 42 nH MTS (Multi-turn, multiple metal layers in Series) inductor.

Collaboration is a key factor in successful knowledge management. Recently, wikis have become a popular solution for distributed and collaborative knowledge management. However, most wikis do not appropriately support the facilities needed for group idea creation and can only represent unstructured knowledge (text, images, and hyperlinks) which cannot be reused or systematized. This paper proposes the use of a Spatial Hypertext Wiki (ShyWiki) as a knowledge management wiki which allows users to interact in a distributed and collaborative way in order to generate ideas, and organize and structure knowledge. This type of wiki can help in the externalization of tacit knowledge, and is able to represent explicit knowledge at different levels of formality. Furthermore, the visual and spatial characteristics of this wiki can be used for representing implicit relations among concepts as well as for organizing and visualizing knowledge.

In this paper, we present the WCIP iterative procedure (wave concept iterative procedure) for solving continuity conditions in terms of waves rather than in term of tangential fields providing a mixed resolution in spatial and spectral domain taking the best advantage of each resolution domain and lower computation time. The spiral inductor with patterned ground shield is taken as an example of multi-layer structures; the results are in reasonably good agreement with the experimental data.

In this paper, we used the method of problem-based learning (PBL) to integrate the concept of knowledge management, collaborative learning and constructivism. Then, we implemented the method of Problem-based learning via the ADDIE (Analysis, Design, Development, Implementation and Evaluation) model to produce a complete learning process. Finally, this research proposed a Knowledge Management Learning System (KMLS), where it can support learning-process progress and facilitate learners' learning more meaningfully.