Statistical mathematical models are developed for forecasting qualitative indexes of the products of atmospheric block in an atmospheric-and-vacuum distillation unit. Fuzzy logic control algorithmis proposed and analy...
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Statistical mathematical models are developed for forecasting qualitative indexes of the products of atmospheric block in an atmospheric-and-vacuum distillation unit. Fuzzy logic control algorithmis proposed and analyzed for the qualitative indexes;rule database is organized on the basis of expert appraisals. A static mathematical model of the control object is created in UNISIM Design. An approach is suggested for integrating Matlab (including Simulink) and UNISIM Design. Finally, a computing experiment is conducted to assess efficiency of the control algorithm for the qualitative indexes using the mathematical model.
The matrix method for localization of a faulty block that was proposed earlier by the present author was considered as applied to a discrete device with multi-output blocks At that, the question of reducing the amount...
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The matrix method for localization of a faulty block that was proposed earlier by the present author was considered as applied to a discrete device with multi-output blocks At that, the question of reducing the amount of the test hardware was solved by constructing appropriately the matrix of block outputs. An algorithm for such construction was given.
Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithmby using only local phase information. We also demonstrate that local...
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Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithmby using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector;it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm.
A new construction adder based on Chinese abacus algorithm is presented in this paper. There are two kinds of beads used in this construction. Each column element has three higher beads with a weight of four and three...
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A new construction adder based on Chinese abacus algorithm is presented in this paper. There are two kinds of beads used in this construction. Each column element has three higher beads with a weight of four and three lower beads with a weight of one. The proposed 32-bit adder contains eight column elements. The construction was simulated by the technology of TSMC 0.18 mu m CMOS process. Layout was also made by the same technology. The maximum delay of the 32-bit abacus adder is 0.91 ns and 14% less than that of Carry Look-ahead Adders for 0.18 mu m technology. The power consumption of the abacus adder is 3.1 mW and 28% less than that of Carry Look-ahead Adders for 0.18 mu m technology. Recent researches are compared with the proposed adder. The construction was also simulated by Predictive Technology Model. The PTM results also presented. The use of Chinese abacus approach offers a competitive technique with respect to other adders. (C) 2012 Elsevier Ltd. All rights reserved.
Modeling and simulation is essential for performance evaluation of wireless systems and specific algorithms used, for instance, during resource allocation. For Current and future wireless systems, several properties h...
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Modeling and simulation is essential for performance evaluation of wireless systems and specific algorithms used, for instance, during resource allocation. For Current and future wireless systems, several properties have to be considered such as data traffic, frequency selective fading channels, and radio resource management. Throughout this article, a new system-level simulator concept is presented for packet switched systems using OFDMA, which is called snapshot-based SLS;and represents a compromise between state-of-the-art static and dynamic SLSs. The proposed methodology only considers short time intervals within the busy hour by their statistics so that RRM and data traffic can be considered, as in dynamic SLS, but with lower computational complexity. In this article a description is given of how the cellular setup and traffic generation are performed for the proposed snapshot concept. Furthermore, a new methodology is proposed for a quality measure of resource units that is applicable to future wireless systems using an interleaved subcarrier allocation. Exemplary simulation results show that the developed concept is able to evaluate the performance of OFDMA systems considering the impact of, for example, data traffic and resource allocation strategies.
We consider M (greater-than-or-equal-to 2) transmitting stations sending packets to a single receiver over a slotted time-multiplexed link. For each phase consisting of T consecutive slots, the receiver dynamically al...
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We consider M (greater-than-or-equal-to 2) transmitting stations sending packets to a single receiver over a slotted time-multiplexed link. For each phase consisting of T consecutive slots, the receiver dynamically allocates these slots among the M transmitters. The cost per slot for holding a packet may vary among the transmitters, and may be interpreted in terms of multiple classes of messages. Our objective is to characterize policies that minimize the discounted and long-term average costs due to holding packets at the M stations, based on delayed information on the numbers of packets being held at the respective transmitters. We derive properties of optimal (discounted) policies that reduce the computational complexity of the optimal How control algorithm. For M = 2, we show that the minimal total cost is convex and submodular in the state, and we prove the following properties of optimal policies: 1) when the state at transmitter i increases by unity while the state at the other transmitter j is fixed, the optimal allocation is either unchanged, or increases by one at transmitter i and decreases hy one at transmitter j;and 2) the optimal policy is of the threshold type. We use these properties to show that the optimization reduces to the calculation of optimal allocations for a finite number of states. In addition, for each such state (excluding the origin), property 1) implies a significant reduction in the computation of optimal allocations. As an application, we further characterize optimal policies when the message generation at the transmitter of higher priority is stochastically larger than the message generation at the other. Under additional restrictions on the average arrival rate and the second moment of the number of arrivals per slot, similar results are derived for optimal policies with time-average costs.
A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM). First, the structure and operating pri...
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A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM). First, the structure and operating principles of the LUSM are introduced. Since the dynamic characteristics and motor parameters of the LUSM are non-linear and time-varying, an RWNN controller is designed to improve the control performance for the precision tracking of various reference trajectories. The network structure and its on-line learning algorithm using delta adaptation law of the RWNN are described in detail. Moreover, the connective weights, translations and dilations of the RWNN are trained on-line. Furthermore, to guarantee the convergence of the tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RWNN. In addition, an FPGA chip is adopted to implement the developed control algorithm for possible low-cost and high-performance industrial applications. Finally, the effectiveness of the proposed control system is verified by some experimental results.
Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward neural network dedicated to an extremely fast learning. However, the performance of ELM in structural impact localization is u...
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Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward neural network dedicated to an extremely fast learning. However, the performance of ELM in structural impact localization is unknown yet. In this paper, a comparison study of ELM with least squares support vector machine (LSSVM) is presented for the application on impact localization of a plate structure with surface-mounted piezoelectric sensors. Both basic and kernel-based ELM regression models have been developed for the location prediction. Comparative studies of the basic ELM, kernel-based ELM, and LSSVM models are carried out. Results show that the kernel-based ELM requires the shortest learning time and it is capable of producing suboptimal localization accuracy among the three models. Hence, ELM paves a promising way in structural impact detection.
The article describes an approach to explore music collections by navigating through different views. The technique used is called aligned self-organizing maps (SOM). The SOM is an unsupervised neural network with app...
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The article describes an approach to explore music collections by navigating through different views. The technique used is called aligned self-organizing maps (SOM). The SOM is an unsupervised neural network with applications in various domains including audio analysis. As a clustering algorithm, the SOM is very similar to other partitioning algorithms such as K-means. In terms of topology preservation for visualization of high-dimensional data, alternatives include multi-dimensional scaling, Sammon's mapping and generative topographic mapping. The objective of the SOM is to map high-dimensional data into two-dimensional map in such a way that similar items are located near each other. The SOM consists of an ordered set of units that are arranged in two-dimensional visualization called the map. Common choices to arrange the map units are rectangular or hexagonal grids. There are two main parameters for the SOM algorithm. One is the map size the other is the final neighborhood radius. A larger map gives a higher resolution of the mapping but is computationally more expensive. The final neighborhood radius defines the smoothness of the mapping and should be adjusted depending on the noise level in the data. The SOM is a useful tool for exploring a data set according to a given similarity measure. An aligned SOM is an extension to the basic SOM that allows for interactively shifting the focus between different aspects and exploring the resulting gradual changes in the organization of the data.
This paper presents a unifying approach for a reliable calculation of all azeotropes and pinch points for homogeneous and heterogeneous non-reactive mixtures. The approach builds on a reformulation of the pinch-equati...
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This paper presents a unifying approach for a reliable calculation of all azeotropes and pinch points for homogeneous and heterogeneous non-reactive mixtures. The approach builds on a reformulation of the pinch-equation system and an efficient continuation algorithm including bifurcation analysis. The calculation of azeotropes is based on an analogy of univolatility curves and the pinch branches for pure component products. The resulting method can efficiently and reliably calculate all homogeneous and heterogeneous non-reactive azeotropes. The only exception would be the existence of isolated univolatility curves inside the composition space, which to the best knowledge of the authors has never been reported. Since the method can further determine the pinch branches and pinch points based on the knowledge of the azeotropes, it presents a self-contained method for calculation of the most important information on nonideal multicomponent mixtures to support process synthesis. The application of the method is illustrated by means of several complex mixtures.
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