This paper considers the SOVA and the Log-MAP for decoding Turbo codes. It primarily studies the differences between the two algorithms and discusses the suitability of combining both algorithms. The frames are first ...
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This paper considers the SOVA and the Log-MAP for decoding Turbo codes. It primarily studies the differences between the two algorithms and discusses the suitability of combining both algorithms. The frames are first applied with SOVA with error detection. After a fixed maximum number of SOVA, the erroneous frames are continued with Log-MAP. The results show that the algorithm could reduce the complexity and keep the performance.
As the aviation community moves toward the Next Generation Air Transportation System (NextGen), the current Traffic Alert and Collision Avoidance System (TCAS II) may become inadequate. This paper presents a novel app...
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As the aviation community moves toward the Next Generation Air Transportation System (NextGen), the current Traffic Alert and Collision Avoidance System (TCAS II) may become inadequate. This paper presents a novel approach to detection and resolution of air traffic conflicts in a 3-dimensional (3-D) airspace between two aircraft. The inputs to the detection algorithm are the current 3-D position and speed vector of both aircraft and a cylindrical minimum safety protection zone (PZ). For collision avoidance systems (CASs), the size of the configurable PZ can be assigned values that the Federal Aviation Administration (FAA) considers as a near mid air collision (NMAC 1 ) incident. When available, additional inputs, such as measurement uncertainties and intruder type (e.g., manned/unmanned), can be used to alter the default protection zone. The conflict detection takes into account the 3-D encounter (e.g., closure rate, miss distance, relative converging maneuver). The resolution algorithm initially computes a set of six resolution advisories (RAs) and associated resolution alert times that ensure no violation of the protection zone. Two solutions are computed for each of the three dimensions: ground track, ground speed, and vertical speed. The initial resolution advisories (RAs) solutions take into account ownship capability (i.e., max climb/descent rate, max turn rate, max speed/stall speed) and ownship pilot response delay (e.g., autonomous vs. manual RA execution). These six solutions are subsequently down-selected in two steps: first, based on the encounter geometry, a single implicitly coordinated, independent solution is selected for each of the three dimensions; then, based on ownship preferences and operational considerations a final RA solution is computed.
The design of synchronous multiphase DC-DC converters allows improvements of the characteristics of high power systems. The automotive industry forecast that future power demands inside a car will oscillate between 2....
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The design of synchronous multiphase DC-DC converters allows improvements of the characteristics of high power systems. The automotive industry forecast that future power demands inside a car will oscillate between 2.5 kW and 3.5kW, keeping a dual system of 42/14V batteries. In this paper, an optimized fuzzy control algorithm has been developed to control a synchronous multiphase converter of 1.6kW for dual voltage architecture in future vehicle applications. The proposed optimized fuzzy control algorithm is analyzed and simulated together with a non lineal model of the power stage, by means of Matlab and Simulink. This simulation platform also integrates tools for a future implementation of the controller embedded in a FPGA. The main contribution of this work is the implementation of an optimized fuzzy algorithm of control that can be used independently of the number of phases of the converter, making it suitable to be applied in a wide range of high power applications. This algorithm has been designed having in mind the goal of developing a real-time FPGA-based controller, so the complexity has been reduced to a minimum. Hybrid vehicles, aerospace and naval industry power systems can also benefit from the development of this algorithm.
With the ever-increasing wireless multicast data applications recently, considerable efforts have focused on the large scale heterogeneous wireless multicast, especially those with large propagation delays, which mean...
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With the ever-increasing wireless multicast data applications recently, considerable efforts have focused on the large scale heterogeneous wireless multicast, especially those with large propagation delays, which means the feedbacks arriving at the source node are somewhat outdated and harmful to the control actions. To attack the above problem, this paper describes a novel, autonomous, and predictive wireless multicast flow control scheme, the so-called proportional, integrative plus neural network (PINN) predictive technique, which includes two components: the PI flow controller located at the wireless multicast source has explicit rate algorithm to regulate the transmission rate; and the neural network part located at the middle branch node predicts the available buffer occupancy for those longer delay receivers. The ultimate sending rate of the multicast source is the expected receiving rates computed by PI controller based on the consolidated feedback information, and it can be accommodated by its participating branches. This network-assisted property is different from the existing control schemes in that neural network controller can predict the buffer occupancy caused by those long delay receivers, which probably cause irresponsiveness of a wireless multicast flow. This active scheme makes the control more responsive to the network status, therefore, the rate adaptation can be in a timely manner for the sender to react to network congestion quick. We analyze the theoretical aspects of the proposed algorithm, show how the control mechanism can be used to design a controller to support wireless multi-rate multicast transmission based on feedback of explicit rates.
Applied in tunnel microwave heating system, single input single output fuzzy-self-setting PID algorithm has many restrictions because such system has close coupled property. Thus fuzzy decoupling algorithm is raised. ...
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Applied in tunnel microwave heating system, single input single output fuzzy-self-setting PID algorithm has many restrictions because such system has close coupled property. Thus fuzzy decoupling algorithm is raised. Such decoupling algorithm can decrease or even eliminate the coupling of the variables in this system. The stability of the system can also be improved. Discussion over the developing of control firmware and upper-monitor interface is also included on the basis of the existing hardware platform. The efficiency and effectiveness of the designed control algorithm is mainly considered in this paper.
Several objective functions for vector field segmentation are presented. Y. G. Leclerc's (1989) MRF (Markov random field) model is extended by the addition of information-theoretic penalties for regions and distin...
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Several objective functions for vector field segmentation are presented. Y. G. Leclerc's (1989) MRF (Markov random field) model is extended by the addition of information-theoretic penalties for regions and distinct means. Standard methods of signal detection and estimation are used to develop a theoretical performance analysis which quantitatively predicts the performance at realistic noise levels. The theoretical performance analysis demonstrates the need for qualitative change from the scalar case; separate penalties for boundary structure and region existence are very beneficial for high d (dimensional). The theoretical analysis also indicates the merit of an objective function before an optimization algorithm has been developed. It also serves as a benchmark for optimization algorithm performance. Theoretical and experimental results agree fairly well.< >
Genetic algorithms (GA) have been applied in many fields to solve multivariable, non linear optimization problems. There are lots of different GA techniques which are used to improve the performance of the algorithm. ...
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Genetic algorithms (GA) have been applied in many fields to solve multivariable, non linear optimization problems. There are lots of different GA techniques which are used to improve the performance of the algorithm. In this paper, the implementation of GA in optimization of electrical system design for offshore wind farms is proposed and several different GA techniques are investigated. The main problems of GA implementation in this field are addressed and the suitable GA techniques are proposed. The GA method is applied to a real offshore wind farm and the results are evaluated. It is concluded that the genetic algorithm is suitable for the optimization of offshore wind farm layout design as long as proper GA techniques are employed
Ultra wide band (UWB) is an ideal candidate for achieving high data rates over short distances with low cost and low power consumption. In this paper, we propose a simple pulse design method that uses the iterative co...
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Ultra wide band (UWB) is an ideal candidate for achieving high data rates over short distances with low cost and low power consumption. In this paper, we propose a simple pulse design method that uses the iterative combination of five Rayleigh derivatives to meet the FCC UWB indoor spectral mask requirements. The performance comparison between the combination pulse and the second derivative Gaussian pulse is also presented by means of the computer simulation. The simulation results show that the power spectrum density (PSD) of the combination pulse approaches the FCC spectral mask obviously, and the performances of UWB system using combination pulse are better than that using the second derivative Gaussian pulse.
In this paper, we propose and analyze a new GPS positioning algorithm. Our algorithm uses the direct linearization technique to reduce the computation time overhead. We invoke the general least squares method in order...
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ISBN:
(纸本)9781424472611
In this paper, we propose and analyze a new GPS positioning algorithm. Our algorithm uses the direct linearization technique to reduce the computation time overhead. We invoke the general least squares method in order to achieve optimality in the situation when the trilateration system of equations becomes over-determined. We systematically evaluate our new algorithms and show that they indeed take much less computation time than the traditional GPS method while maintaining reasonable accuracy.
This paper proposes advanced key performance indicators dedicated to learning machines and auto-adaptive systems performance analysis. This work introduces an algorithm implementing designed key performance indicators...
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This paper proposes advanced key performance indicators dedicated to learning machines and auto-adaptive systems performance analysis. This work introduces an algorithm implementing designed key performance indicators for automatic learning capacity checking. The algorithm simulates the supervised environment to stimulate the tested auto-adaptive machine and then study its adaption capacity based on indicators statistically designed.
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