LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

An automated coding and classification system with supporting database for effective design of manufacturing systems

The philosophy of group technology (GT) is an important concept in the design of flexible manufacturing systems and manufacturing cells. Group technology is a manufacturing philosophy that identifies similar parts and groups them into families. Beside assigning unique codes to these parts, group technology developers intend to take advantage of part similarities during design and manufacturing processes. GT is not the answer to all manufacturing problems, but it is a good management technique with which to standardize efforts and eliminate duplication. Group technology classifies parts by assigning them to different families based on their similarities in: (1) design attributes (physical shape and size), and/or (2) manufacturing attributes (processing sequence). The manufacturing industry today is process focused; departments and sub units are no longer independent but are interdependent. If the product development process is to be optimized, engineering and manufacturing cannot remain independent any more: they must be coordinated. Each sub-system is a critical component within an integrated manufacturing framework. The coding and classification system is the basis of CAPP and the functioning and reliability of CAPP depends on the robustness of the coding system. The proposed coding system is considered superior to the previously proposed coding systems, in that it has the capability to migrate into multiple manufacturing environments. This article presents the design of a coding and classification system and the supporting database for manufacturing processes based on both design and manufacturing attributes of parts. An interface with the spreadsheet will calculate the machine operation costs for various processes. This menu-driven interactive package is implemented using dBASE-IV. Part Family formation is achieved using a KAMCELL package developed in TURBO Pascal.     

Electronic data acquisition forms in construction management

Effective management of construction projects depends on good access to and control of data, especially data pertaining to cost and schedule control functions. However, the proper design and development of automated mechanisms have not had the facility to acquire and store quality data in a timely manner. The purpose of this paper, then, is to discuss a prototype, automated data acquisition system that was developed to support an integrated project management system. The data acquisition system is composed of an integrated set of electronic forms used in conjunction with a bar coding data-entry tool.     

Response coding and visuomotor transformation in the Simon task: The role of action goals.

Manual responses can be defined by differing response parameters. Any of them may generate a Simon effect. For all those response parameters, the same implementation of the Simon effect (in terms of subserving mechanism) is assumed. In 3 experiments, subjects had to respond with either fingers or sticks. Temporal properties of the Simon effect changed with response parameters relevant in a task. The Simon effect for manual responses decayed. For stick responses, in which the action goal differed from the anatomical mapping of the acting hand, a sustained Simon effect was observed. However, if the action goal for stick responses was not instrumental for selecting the correct response, the Simon effect decayed. The findings are consistent with the notion of different mechanisms involved in generating a Simon effect. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An orthogonal basis for the hyperbolic hybrid polynomial space

Motivated by the wide usage of the Tchebyshev basis and Legendre basis in the algebra polynomial space, we construct an orthogonal basis with the properties of the H-Bézier basis in the hyperbolic hybrid polynomial space, which is similar to the Legendre basis and holds remarkable properties. Moreover, we derive the transformation matrices that map the H-Bézier basis and the orthogonal basis forms into each other. An example for approximating the degree reduction of the H- Bézier curves is sketched to illustrate the utility of the orthogonal basis.     

Vote counting measures for ensemble classifiers

Various measures, such as Margin and Bias/Variance, have been proposed with the aim of gaining a better understanding of why Multiple Classifier Systems (MCS) perform as well as they do. While these measures provide different perspectives for MCS analysis, it is not clear how to use them for MCS design. In this paper a different measure based on a spectral representation is proposed for two-class problems. It incorporates terms representing positive and negative correlation of pairs of training patterns with respect to class labels. Experiments employing MLP base classifiers, in which parameters are fixed but systematically varied, demonstrate the sensitivity of the proposed measure to base classifier complexity.     

用分数延迟改进基音预测的CELP编码方案

在ＣＥＬＰ编码器中，通常用延迟为抽样间隔整数倍的长项预测器表征浊音语音的准周期性，然而在低比特率，这种限制降低了编码器的性能。本文在介绍了ＣＥＬＰ编码器原理及激励码本构成后，重点研究了一种新型的基音预测方法；分数延迟基音预测，计算机模拟结果表明，这种方法能对浊音进行更准确的表达，尤其对女性讲话者明显改善了语音质量。     

On the design of multiple key hashing files for concurrent orthogonal range retrieval between two disks

This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.

A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system.     

Age effects in coding tasks: Componential analysis and test of the sensory deficit hypothesis.

Multiple forms of a symbol-digit substitution task were used to provide a componential analysis of age differences in coding task performance. The results demonstrated age differences in feature encoding, memory, and visual search. A 2nd experiment was conducted with young adults to investigate a sensory deficit as a locus of age differences. The spatial contrast sensitivity deficit of older adults was simulated on forms by applying a digital filter. Persons in the age-simulated contrast condition performed worse than those in the normal contrast condition. The stimulus degradation effect was linked to visual search speed. The study illustrates the utility of componential analysis and offers direct support for the hypothesis that sensory deficits affect performance on tasks used to assess intelligence (PsycINFO Database Record (c) 2010 APA, all rights reserved)