Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hy...Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hysteresis loop that exists in the actual maneuvering process of the aircraft.Here,an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces with any motion in the amplitude and frequency ranges based on the Least Squares Support Vector Machines(LS-SVMs).In the selection of the input form,avoiding the use of reduced frequency as a parameter makes the model more universal.After model training is completed,the method is applied to predict the lift coefficient,drag coefficient and pitching moment coefficient of the RAE2822 airfoil,in sine and sweep motions under the conditions of plunging and pitching at Mach number 0.8.The predicted results of the initial unstable process and the final stable process are in close agreement with the Computational Fluid Dynamics(CFD)data,demonstrating the feasibility of the model for nonlinear unsteady aerodynamics modeling and the effectiveness of the input design approach.展开更多
为缓解负偏置温度不稳定性(negative bias temperature instability,NBTI)效应引起的电路老化,提高电路可靠性,提出一种在电路待机状态下应用输入向量约束的门替换方法.运用动态和静态的NBTI模型进行感知NBTI的静态时序分析,确定潜在关...为缓解负偏置温度不稳定性(negative bias temperature instability,NBTI)效应引起的电路老化,提高电路可靠性,提出一种在电路待机状态下应用输入向量约束的门替换方法.运用动态和静态的NBTI模型进行感知NBTI的静态时序分析,确定潜在关键路径,考虑路径相关性的关键门算法以确定关键门,并生成能使关键门最大限度处于恢复阶段的输入向量.对输入向量无法控制的关键门采用门替换方法进行内部控制.对ISCAS标准电路的实验结果表明,电路时序余量为5%时,该方法的平均门替换率降低到9.68%,时延改善率提高到39.65%.展开更多
This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the ...This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the conventional TAS algorithms need to search all possible legitimate antenna subsets, they may impose some redundant calculations. In order to avoid this problem, we employ some pattern recognition methods to carry out the TAS algorithm in this paper. To be specific, two PR algorithms, namely the K-Nearest Neighbor (KNN) algorithm and the Support Vector Machine (SVM) algorithm, are introduced and redesigned to obtain a TAS with lower complexity but higher efficiency. Moreover, in order to improve the performance of the SVM, we propose a new feature extraction of channel matrix for the TAS. Our simulation results show that the proposed KNN and SVM based PR-TAS algorithms are capable of striking a flexible tradeoff between the complexity and the Bit Error Rate (BER), and the new feature can effectively improve the BER performance compared with the conventional feature extraction method.展开更多
It is obviously advantageous to use single-pattern cell ternary tree (T-gate)network to obtain ternary logic function. Many scholars at home and abroad have done much in minimization of T-gate realization of multiple-...It is obviously advantageous to use single-pattern cell ternary tree (T-gate)network to obtain ternary logic function. Many scholars at home and abroad have done much in minimization of T-gate realization of multiple-valued logic. It is generally acknowledged that it is necessary to try N! times in order to get an optimal result. However, using the Input Vector Map presented here, which is as simple and convenient as Binary Karnaugh Map, we can get an optimal result by trying only N times.展开更多
we demonstrate the adjustability of optimal input power(OIP) of the radio over fiber(RoF) link by proper link gain control in the central unit(CU) and remote antenna unit(RAU).The experiment results show that the read...we demonstrate the adjustability of optimal input power(OIP) of the radio over fiber(RoF) link by proper link gain control in the central unit(CU) and remote antenna unit(RAU).The experiment results show that the reading and writing distance(RWD)of the radio frequency identification(RFID)service and the throughput of the WiFi service have a max increase of 3cm and 6.975Mbit/s respectively when the OIP value equals to output power of commercial products,compared with OIP value with 5-dBm right/left shift to the output power.展开更多
The application of support vector machines to forecasting problems is becoming popular, lately. Several comparisons between neural networks trained with error backpropagation and support vector machines have shown adv...The application of support vector machines to forecasting problems is becoming popular, lately. Several comparisons between neural networks trained with error backpropagation and support vector machines have shown advantage for the latter in different domains of application. However, some difficulties still deteriorate the performance of the support vector machines. The main one is related to the setting of the hyperparameters involved in their training. Techniques based on meta-heuristics have been employed to determine appropriate values for those hyperparameters. However, because of the high noneonvexity of this estimation problem, which makes the search for a good solution very hard, an approach based on Bayesian inference, called relevance vector machine, has been proposed more recently. The present paper aims at investigating the suitability of this new approach to the short-term load forecasting problem.展开更多
In a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Local Area Network (WLAN) system, both Access Points (APs) and Mobile Termi-nals (MTs) are configured with mu...In a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Local Area Network (WLAN) system, both Access Points (APs) and Mobile Termi-nals (MTs) are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine (LS-SVM) based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.展开更多
Two novel schemes of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the first scheme, T2 zero row vectors are added into conven...Two novel schemes of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the first scheme, T2 zero row vectors are added into conventional unitary matrices directly, and the number of new unitary matrices obtained by different positions of the added zero vectors in T symbol duration is [T / T2 ] times larger than that of conventional unitary matrices. In the second scheme, one part of the required constellations is created by the first scheme and the other part is obtained by the conventional design. This means that more information bits can be transmitted by the new constellations. According to their special construction, two corresponding decoding algorithms are proposed with low complexity in flat fading channel, respectively. At the same time, the probability of miss detection is deduced for the decoding algorithms. Performance analysis and simulation results show that the proposed constellations outperform the conventional constellations and the proposed decoding algorithms are efficient and simple.展开更多
The Brazilian electric sector reform established that the remuneration of distribution utilities must be through the management of their systems. This fact increased the necessity of control and management of load flo...The Brazilian electric sector reform established that the remuneration of distribution utilities must be through the management of their systems. This fact increased the necessity of control and management of load flows through the connection points between the distribution systems and the basic grid as a function of the contracted amounts. The objective of this control is to avoid that these flows exceed some thresholds along the contracted values, avoiding monetary penalties to the utility or unnecessary amounts of contracted flows that overrates the costumers. This question highlights the necessity of forecast the flows in these connection points in sufficient time to permit the operator to take decisions to avoid flows beyond the contracted ones. In this context, this work presents the development of a neural network based load flow forecaster, being tested two time-series neural models： support vector machines and Bayesian inference applied to multilayered perceptron. The models are applied to real data from a Brazilian distribution utility.展开更多
文摘Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hysteresis loop that exists in the actual maneuvering process of the aircraft.Here,an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces with any motion in the amplitude and frequency ranges based on the Least Squares Support Vector Machines(LS-SVMs).In the selection of the input form,avoiding the use of reduced frequency as a parameter makes the model more universal.After model training is completed,the method is applied to predict the lift coefficient,drag coefficient and pitching moment coefficient of the RAE2822 airfoil,in sine and sweep motions under the conditions of plunging and pitching at Mach number 0.8.The predicted results of the initial unstable process and the final stable process are in close agreement with the Computational Fluid Dynamics(CFD)data,demonstrating the feasibility of the model for nonlinear unsteady aerodynamics modeling and the effectiveness of the input design approach.
文摘为缓解负偏置温度不稳定性(negative bias temperature instability,NBTI)效应引起的电路老化,提高电路可靠性,提出一种在电路待机状态下应用输入向量约束的门替换方法.运用动态和静态的NBTI模型进行感知NBTI的静态时序分析,确定潜在关键路径,考虑路径相关性的关键门算法以确定关键门,并生成能使关键门最大限度处于恢复阶段的输入向量.对输入向量无法控制的关键门采用门替换方法进行内部控制.对ISCAS标准电路的实验结果表明,电路时序余量为5%时,该方法的平均门替换率降低到9.68%,时延改善率提高到39.65%.
基金the Important National Science and Technology Specific Projects of China under Grant 2018ZX03001001the National Science Foundation of China under Grant number 61501095.
文摘This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the conventional TAS algorithms need to search all possible legitimate antenna subsets, they may impose some redundant calculations. In order to avoid this problem, we employ some pattern recognition methods to carry out the TAS algorithm in this paper. To be specific, two PR algorithms, namely the K-Nearest Neighbor (KNN) algorithm and the Support Vector Machine (SVM) algorithm, are introduced and redesigned to obtain a TAS with lower complexity but higher efficiency. Moreover, in order to improve the performance of the SVM, we propose a new feature extraction of channel matrix for the TAS. Our simulation results show that the proposed KNN and SVM based PR-TAS algorithms are capable of striking a flexible tradeoff between the complexity and the Bit Error Rate (BER), and the new feature can effectively improve the BER performance compared with the conventional feature extraction method.
文摘It is obviously advantageous to use single-pattern cell ternary tree (T-gate)network to obtain ternary logic function. Many scholars at home and abroad have done much in minimization of T-gate realization of multiple-valued logic. It is generally acknowledged that it is necessary to try N! times in order to get an optimal result. However, using the Input Vector Map presented here, which is as simple and convenient as Binary Karnaugh Map, we can get an optimal result by trying only N times.
基金supported in part by the National Basic Research Program of China （2012CB315704） the National Natural Science Foundation of China（No.61275068） the Key Grant Project of Chinese Ministry of Education（No.313049）
文摘we demonstrate the adjustability of optimal input power(OIP) of the radio over fiber(RoF) link by proper link gain control in the central unit(CU) and remote antenna unit(RAU).The experiment results show that the reading and writing distance(RWD)of the radio frequency identification(RFID)service and the throughput of the WiFi service have a max increase of 3cm and 6.975Mbit/s respectively when the OIP value equals to output power of commercial products,compared with OIP value with 5-dBm right/left shift to the output power.
文摘The application of support vector machines to forecasting problems is becoming popular, lately. Several comparisons between neural networks trained with error backpropagation and support vector machines have shown advantage for the latter in different domains of application. However, some difficulties still deteriorate the performance of the support vector machines. The main one is related to the setting of the hyperparameters involved in their training. Techniques based on meta-heuristics have been employed to determine appropriate values for those hyperparameters. However, because of the high noneonvexity of this estimation problem, which makes the search for a good solution very hard, an approach based on Bayesian inference, called relevance vector machine, has been proposed more recently. The present paper aims at investigating the suitability of this new approach to the short-term load forecasting problem.
文摘In a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) based Wireless Local Area Network (WLAN) system, both Access Points (APs) and Mobile Termi-nals (MTs) are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine (LS-SVM) based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.
文摘Two novel schemes of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the first scheme, T2 zero row vectors are added into conventional unitary matrices directly, and the number of new unitary matrices obtained by different positions of the added zero vectors in T symbol duration is [T / T2 ] times larger than that of conventional unitary matrices. In the second scheme, one part of the required constellations is created by the first scheme and the other part is obtained by the conventional design. This means that more information bits can be transmitted by the new constellations. According to their special construction, two corresponding decoding algorithms are proposed with low complexity in flat fading channel, respectively. At the same time, the probability of miss detection is deduced for the decoding algorithms. Performance analysis and simulation results show that the proposed constellations outperform the conventional constellations and the proposed decoding algorithms are efficient and simple.
文摘The Brazilian electric sector reform established that the remuneration of distribution utilities must be through the management of their systems. This fact increased the necessity of control and management of load flows through the connection points between the distribution systems and the basic grid as a function of the contracted amounts. The objective of this control is to avoid that these flows exceed some thresholds along the contracted values, avoiding monetary penalties to the utility or unnecessary amounts of contracted flows that overrates the costumers. This question highlights the necessity of forecast the flows in these connection points in sufficient time to permit the operator to take decisions to avoid flows beyond the contracted ones. In this context, this work presents the development of a neural network based load flow forecaster, being tested two time-series neural models： support vector machines and Bayesian inference applied to multilayered perceptron. The models are applied to real data from a Brazilian distribution utility.
