An adaptive neural fuzzy filter and its applications

A new kind of nonlinear adaptive filter, the adaptive neural fuzzy filter (ANFF), based upon a neural network's learning ability and fuzzy if-then rule structure, is proposed in this paper. The ANFF is inherently a feedforward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules. The adaptation here includes the construction of fuzzy if-then rules (structure learning), and the tuning of the free parameters of membership functions (parameter learning). In the structure learning phase, fuzzy rules are found based on the matching of input-output clusters. In the parameter learning phase, a backpropagation-like adaptation algorithm is developed to minimize the output error. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially, and both the structure learning and parameter learning are performed concurrently as the adaptation proceeds. However, if some linguistic information about the design of the filter is available, such knowledge can be put into the ANFF to form an initial structure with hidden nodes. Two major advantages of the ANFF can thus be seen: 1) a priori knowledge can be incorporated into the ANFF which makes the fusion of numerical data and linguistic information in the filter possible; and 2) no predetermination, like the number of hidden nodes, must be given, since the ANFF can find its optimal structure and parameters automatically     

Broadband Microwave Measurements of Overdoped Y0.9Ca0.1Ba2Cu3O7−δ Films Using Corbino Geometry

The surface impedance of Y_0.9Ca_0.1Ba₂Cu₃O_7?δ thin films was measured using the Corbino spectroscopy method. This special geometry, in which the sample dimensions are well defined by a ring pattern, is ideal for broadband high frequency reflection measurements. Using the complex reflected signal, S ₁₁, measured by a vector network analyzer, one can find the surface impedance of the thin film, from which the complex conductivity can be deduced. In the current work we present the three-standard approach for calibration of the Corbino method and demonstrate the benefits of this approach in measuring superconducting Y_0.9Ca_0.1Ba₂Cu₃O_7?δ thin films up to 20 GHz and down to 6 K. For the data analysis the well-known generalized two-fluid model was implemented, taking into account a film thickness which is much smaller than the normal state skin depth and superconducting penetration depth.     

Tribological impact of touchdown detection on bit patterned media robustness

Touchdown detection by thermal-flying height control (TFC) has been implemented to calibrate flying height (FH) of magnetic sliders for all hard disk drives. For bit patterned media (BPM) to be successful as a revolutionary technology to further increase recording areal density, it must experience the touchdown process with similar robustness as conventional continuous media. Here we numerically study the tribological impact of TFC touchdown detection on the continuous media and unplanarized BPM by three-dimensional (3D) transient finite-element models with the frictional heating and thermal-elastic-plastic materials included. Our results demonstrate that the continuous media exhibits no plastic deformation due to the TFC touchdown with an over-push as large as 2 nm, whereas the plastic strain of the BPM may reach 3 % at higher sliding velocities, and it exists over a wide range of bulge radius and disk velocity. Such plastic deformation can lead to permanent media damage and data loss. Besides, the temperature rise of the BPM (~27 K) is approximately 1.3 times of that of the continuous media (~21 K), and may have to be considered when designing a robust head-disk interface for BPM. Although planarization may improve slider’s flyability performance, our analysis shows that planarizing BPM with SiO₂ deteriorates the tribological robustness of the media in particular at a high disk velocity probably due to the inhomogeneous composition and mismatch of material properties between the filling material and recording material. Hence extreme caution must be exercised when choosing a filling material.     

A computational algorithm for catalysts experiencing concentration‐dependent deactivation

Abstract

A computational algorithm is proposed for catalyst pellets or reactors experiencing concentration‐dependent deactivation. In the integration of the deactivation equation in each time interval, the concentration of poison, reactant or/and product is considered to be a constant. The value of concentration is recalculated from the mass balance equation before integrating the deactivation equation. By such an approach, the number of equations is reduced; thus a two‐dimensional problem can be converted to a single‐dimensional one.     

以L-酒石酸正己酯-硼酸配合物为反相液相色谱手性流动相添加剂分离班布特罗和妥洛特罗

以L-酒石酸正己酯-硼酸配合物为流动相添加剂,采用反相高效液相色谱法分离了班布特罗和妥洛特罗2种手性β-受体激动剂。实验考察了酒石酸正己酯和硼酸的浓度,缓冲溶液的种类、浓度、pH值,有机改性剂甲醇的含量对手性分离效果的影响。在最佳手性分离条件下,班布特罗和妥洛特罗均可以达到基线分离。     

Pattern recognition using a family of design algorithms based uponthe generalized probabilistic descent method

This paper provides a comprehensive introduction to a novel approach to pattern recognition which is based on the generalized probabilistic descent method (GPD) and its related design algorithms. The paper contains a survey of recent recognizer design techniques, the formulation of GPD, the concept of minimum classification error learning that is closely related to the GPD formalization, a relational analysis between GPD and other important design methods, and various embodiments of GPD-based design, including segmental-GPD, minimum spotting error training, discriminative utterance verification, and discriminative feature extraction. GPD development has its origins in basic pattern recognition and Bayes decision theory. It represents a simple but careful re-investigation of the classical theory and successfully leads to an innovative framework. For clarity of presentation, detailed discussions about its embodiments are provided for examples of speech pattern recognition tasks that use a distance-based classifier. Experimental results in speech pattern recognition tasks clearly demonstrate the remarkable utility of the family of GPD-based design algorithms     

Transient Characteristics of Nanoscale Air Bearings Subjected to Joule Heating

Transient characteristic of heat exchange between closely positioned bodies has become an important issue owing to the continuous miniaturization of many technologies such as high-density magnetic recording, integrated circuits, and atomic force microscopy. We experimentally and numerically study the transient characteristics of nanoscale air bearings subjected to Joule heating of a nearby heating element in hard disk drives. Our results reveal that the response consists of multiple characteristic times, and at least two terms (τ ₁ = 162 μs and τ ₂ = 23 μs) are required to capture the transient response. We present a one-dimensional analytical model that provides a better understanding of the nature of the transient characteristics and an efficient way to obtain their trends and bounds. Our model may also explain the much faster response due to laser heating observed in heat-assisted magnetic recording system.     

Analysis and measurement of lateral elliptic motion effect for an asymmetric disc-type ultrasonic motor

This paper presents an analysis and measurement method for studying lateral elliptic motion effect of an asymmetric disc-type ultrasonic motor whose stator is a circular disc with a bonded PZT plate serving as a drive. At the edge of the stator with a simple, fixed three-point support of a 120°–90°–150° configuration, there exists a coupled vibration wave with lateral elliptical motion so as to generate a driving force between the stator and the rotor. The equations of the lateral elliptic motion and the driving force are analytically formulated based on the wave equation on the circular plate, thereby obtaining the driving frequency and the revolution speed of the motor. The relationship between the ultrasonic stator and its boundary condition is investigated as well. The analysis shows that the circumferential edge with a 90° included angle is an optimal contact section for the placement of the rotor. Experiments using the laser vibrometer and photodetector are used to show the validity of the proposed analysis method.     

Combination of online clustering and Q-value based GA for reinforcement fuzzy system design

This paper proposes a combination of online clustering and Q-value based genetic algorithm (GA) learning scheme for fuzzy system design (CQGAF) with reinforcements. The CQGAF fulfills GA-based fuzzy system design under reinforcement learning environment where only weak reinforcement signals such as "success" and "failure" are available. In CQGAF, there are no fuzzy rules initially. They are generated automatically. The precondition part of a fuzzy system is online constructed by an aligned clustering-based approach. By this clustering, a flexible partition is achieved. Then, the consequent part is designed by Q-value based genetic reinforcement learning. Each individual in the GA population encodes the consequent part parameters of a fuzzy system and is associated with a Q-value. The Q-value estimates the discounted cumulative reinforcement information performed by the individual and is used as a fitness value for GA evolution. At each time step, an individual is selected according to the Q-values, and then a corresponding fuzzy system is built and applied to the environment with a critic received. With this critic, Q-learning with eligibility trace is executed. After each trial, GA is performed to search for better consequent parameters based on the learned Q-values. Thus, in CQGAF, evolution is performed immediately after the end of one trial in contrast to general GA where many trials are performed before evolution. The feasibility of CQGAF is demonstrated through simulations in cart-pole balancing, magnetic levitation, and chaotic system control problems with only binary reinforcement signals.