A technique to approximate the solutions of nonlinear Klein–Gordon equation and Klein–Gordon-Schrödinger equations is presented separately. The approach is based on collocation of cubic B-spline functions. The above-mentioned equations are decomposed into a system of partial differential equations, which are further converted to an amenable system of ODEs. The obtained system has been solved by SSP-RK54 scheme. Numerical solutions are presented for five examples, to show the accuracy and usefulness of proposed approach. The approximate solutions of both the equations are computed without using any transformation and linearization. The technique can be applied with ease to solve linear and nonlinear PDEs and also reduces the computational work. 相似文献
In this paper, a novel pyramid coding based rate control scheme is proposed for video streaming applications constrained by a constant channel bandwidth. To achieve the target bit rate with the best quality, the initial quantization parameter (QP) is determined by the average spatio-temporal complexity of the sequence, its resolution and the target bit rate. Simple linear estimation models are then used to predict the number of bits that would be necessary to encode a frame for a given complexity and QP. The experimental results demonstrate that the proposed rate control scheme significantly outperforms the existing rate control scheme in the Joint Model (JM) reference software in terms of Peak Signal to Noise Ratio (PSNR) and consistent perceptual visual quality while achieving the target bit rate. Finally, the proposed scheme is validated through experimental evaluation over a miniature test-bed.
Limb repositioning is necessary for individuals with severe physical disabilities to sustain muscle strength and prevent pressure sores. As robotic technologies become ubiquitous, these tools offer promise to support the repositioning process. However, research has yet to focus on ways in which individuals with severe physical disabilities can control robots for these tasks. This paper presents a study that examines the needs and attitudes of potential users with physical disabilities to control a robotic aid for limb repositioning. Subjects expressed interest in using brain–computer interface (BCI) and speech recognition technologies for purposes of executing robotic tasks. The performance of four subjects controlling arm movements on an avatar through the keyboard, mouse, BCI, and Dragon NaturallySpeaking speech recognition was evaluated. Although BCI and speech technologies may limit physical fatigue, more challenges were faced using BCI and speech conditions compared to the keyboard and mouse. This research promotes accessibility into mainstream robotic technologies and represents the first step in the development of a robotic prototype using a BCI and speech recognition technologies for limb repositioning. 相似文献
A C-coloured graph is a graph, that is possibly directed, where the edges are coloured with colours from the set C. Clique-width is a complexity measure for C-coloured graphs, for finite sets C. Rank-width is an equivalent complexity measure for undirected graphs and has good algorithmic and structural properties. It is in particular related to the vertex-minor relation. We discuss some possible extensions of the notion of rank-width to C-coloured graphs. There is not a unique natural notion of rank-width for C-coloured graphs. We define two notions of rank-width for them, both based on a coding of C-coloured graphs by ${\mathbb{F}}^{*}$-graphs—$\mathbb {F}$-coloured graphs where each edge has exactly one colour from $\mathbb{F}\setminus \{0\},\ \mathbb{F}$ a field—and named respectively $\mathbb{F}$-rank-width and $\mathbb {F}$-bi-rank-width. The two notions are equivalent to clique-width. We then present a notion of vertex-minor for $\mathbb{F}^{*}$-graphs and prove that $\mathbb{F}^{*}$-graphs of bounded $\mathbb{F}$-rank-width are characterised by a list of $\mathbb{F}^{*}$-graphs to exclude as vertex-minors (this list is finite if $\mathbb{F}$ is finite). An algorithm that decides in time O(n3) whether an $\mathbb{F}^{*}$-graph with n vertices has $\mathbb{F}$-rank-width (resp. $\mathbb{F}$-bi-rank-width) at most k, for fixed k and fixed finite field $\mathbb{F}$, is also given. Graph operations to check MSOL-definable properties on $\mathbb{F}^{*}$-graphs of bounded $\mathbb{F}$-rank-width (resp. $\mathbb{F}$-bi-rank-width) are presented. A specialisation of all these notions to graphs without edge colours is presented, which shows that our results generalise the ones in undirected graphs. 相似文献
Abstract: Pedestrian detection techniques are important and challenging especially for complex real world scenes. They can be used for ensuring pedestrian safety, ADASs (advance driver assistance systems) and safety surveillance systems. In this paper, we propose a novel approach for multi-person tracking-by-detection using deformable part models in Kalman filtering framework. The Kalman filter is used to keep track of each person and a unique label is assigned to each tracked individual. Based on this approach, people can enter and leave the scene randomly. We test and demonstrate our results on Caltech Pedestrian benchmark, which is two orders of magnitude larger than any other existing datasets and consists of pedestrians varying widely in appearance, pose and scale. Complex situations such as people occluded by each other are handled gracefully and individual persons can be tracked correctly after a group of people split. Experiments confirm the real-time performance and robustness of our system, working in complex scenes. Our tracking model gives a tracking accuracy of 72.8% and a tracking precision of 82.3%. We can further reduce false positives by 2.8%, using Kalman filtering. 相似文献
In this work, a deep learning (DL)-based massive multiple-input multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL-C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi-directional long short-term memory (Bi-LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi-LSTM-based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function-trained Bi-LSTM-based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi-LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short-term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study. 相似文献
Speed control of a DC motor has always been a challenge because of its variable torque. But it becomes more challenging when noise enters the system at its input. Therefore, there is a need of more advanced controllers. In this paper, a multi-resolution proportional integral derivative (MRPID) controller has been proposed to be utilized to control the speed of a DC motor. It works well even in the presence of noise as compared to the conventional PID controller. Also, performance of a PID controller deteriorates when nonlinearity or uncertainty arises in the system. This degraded performance can be improved by utilizing the multi-resolution property of wavelets, which decomposes the error signal into various frequency components. Further, wavelet coefficients of these decompositions are used to generate the control signal for controlling speed of a DC motor. In this paper, performances of a MRPID, a fractional order PID (FOPID) and a conventional PID controllers are compared in the presence of noise for speed control of a DC motor. The results obtained using a MRPID controller are observed to be better in terms of improved transient characteristics and disturbance rejection for a DC motor as compared to those obtained with PID and FOPID controllers.