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This paper extends the random vector functional-link (RVFL) networks with single-hidden-layer to interval ones (IRVFLNs) with interval model parameters. The analytic solutions are derived for the interval network parameters using the well-known least square methods, which can overcome the problems such as local minimal, slow convergence. In order to evaluate the performance of IRVFLNs, we choose two...
In this paper, we propose an algorithm for estimating the carrier frequency offset (CFO) in OFDM-based multi-cell networks. In 3GPP-LTE single-cell systems, the CFO can be estimated by applying the Schmidl algorithm. However, multi-cell interference (MCI) is induced in multi-cell environments; as a result the MCI degrades estimate accuracy. One solution to mitigate MCI may be via properly designing...
This paper presents the modeling and estimation of state of charge (SoC) for Li-ion batteries using ANFIS architecture. The system consists of two phases of operation. The phase 1 is the SoC modeling process. The phase 2 is the real-time estimation process. Firstly, on the phase-1 operation, a brand-new Li-ion battery is used for a completely discharge cycle which consists of 355 cycles of discharge/charge...
Through carrying on the friction welding to the 45 steel and the W8Co3N high-speed steel and measuring the joint, the data can be obtained which the network simulation need. With fuzzy logic and neural network, we can establish the compensation fuzzy neural network model which has used in the welding process parameter forecast, and carry on the simulation by using it. The result indicates that this...
Cell classification in traffic analysis and modeling is an important task which is required by planning and optimization of mobile networks. Because traffic is always nonlinear, nonstationary and influenced by immeasureable factors, accurate analytical traffic model can be hardly obtained. Therefore a new classification method using reservoir computing to cell types is proposed. Analysis of field...
General object detection still remains a big challenge for vision researchers. In this paper, we are particularly interested in the subject of object detection in the context of street scene. Our image database consists of video frames taken from urban street which tends to be crowded and presents a lot of artificial objects. Traditional street scene understanding methods often involve 3D reconstruction...
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