Search Results - parallel estimation ((((new algorithm) OR (learning algorithm))) OR (_ algorithm))

New algorithm for gyroless spacecraft angular rate Estimation and its application by Abdelrahman, Mohammad, Samaan, Malak A.

“…A new algorithm for estimating the angular velocity using quaternion measurements is developed based on the concept of the global optimality resulting when using a centralized or master Kalman filter. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

“…The new algorithms also boast faster contractions. Both new algorithms performed better than DISOPE. …”
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Resource Minimization in a Real-time Depth-map Processing System on FPGA by Ngo, Huy Tan, Hamid, Nor Hisham, Sebastian , Patrick, Yap, Vooi Voon

“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
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Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz by Ab. Aziz, Ahmad Syahir

“…Therefore, framework development methodology is used to make sure the system successful and can be developed according to the schedule. Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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New CFAR algorithm and circuit development for radar receiver by Kamal, Mustafa Subhi

“…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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Iterative methods for solving split common fixed point problems in Hilbert spaces by Mohammed, Lawan Bulama

“…In other words, we construct parallel and cyclic algorithms for solving the split common fixed point problems for strictly pseudocontractive mappings and prove the convergence results of these algorithms. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…This thesis explains the development of new algorithm for distance measurement using stereo vision sensor. …”
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Early detection of breast cancer using wave elliptic equation with high performance computing by Alias, Norma, Rosly, Nur Syazana, Satam, Noriza, A. Ghaffar, Zarith Safiza, Islam, Md. Rajibul

“…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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Super resolution imaging using modified lanr based on separable filtering by Somadina, Ike Chidiebere

“…The underlying idea is to process and reconstruct information in low and high frequency sub-bands based on separable property of neighbourhood filtering to achieve fast parallel and vectorized operation, while enhancing algorithmic performance by reducing computational burden resulting from computing the weighted function of every pixel for each pixel in an image. …”
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A new approach in solving illumination and facial expression problems for face recognition by Yee, Wan Wong, Kah, Phooi Seng, Li, Minn Ang

“…In this paper, a novel dual optimal multiband features (DOMF) method is presented to increase the robustness of face recognition system to illumination and facial expression variations.The wavelet packet transform first decomposes image into low-, mid- and high-frequency subbands and the multiband feature fusion technique is incorporated to select the subbands that are invariant to illumination and expression variation separately.These subbands form the optimal feature sets.Parallel radial basis function neural networks are employed to classify these feature sets.The scores generated by the neural networks are combined by an adaptive fusion mechanism where the level of illumination variations of the testing image is estimated and the weights are assigned to the scores accordingly.The experimental results show that DOMF outperforms other algorithms and also achieves promising performance on illumination and facial expression variation conditions.…”
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A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling by Purnomo, Muhammad Ridwan Andi, Abdul Wahab, Dzuraidah, Hassan, Azmi, Rahmat, Riza Atiq

“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

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Forward masking threshold estimation using neural networks and its application to parallel speech enhancement by Gunawan, Teddy Surya, Khalifa, Othman Omran, Ambikairajah, Eliathamby

“…Objective measures using PESQ demonstrates that our proposed forward masking model, provides significant improvements (5-15 %) over four existing models, when tested with speech signals corrupted by various noises at very low signal to noise ratios. Moreover, a parallel implementation of the speech enhancement algorithm was developed using Matlab parallel computing toolbox.…”
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A new method for decreasing cell-load variation in dynamic cellular manufacturing systems by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol, Baharudin, Btht Hang Tuah, Leman, Zulkiflle

“…Cell load variation is considered a significant shortcoming in scheduling of cellular manufacturing systems. In this article, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. …”
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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems by Talebpour, Faraz

“…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

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A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty by Delgoshaei, Aidin, Ali, Ahad, Ariffin, Mohd Khairol Anuar, Gomes, Chandima

“…In this paper the impact of inflation on cell-load variation in cellular manufacturing systems is examined. For this purpose, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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A bit-serial sum of absolute difference accelerator for variable block size motion estimation of H.264 by Fatemi, M.R.H., Ates, H.F., Salleh, R.

“…Due to the bit-serial pipeline architecture and using small processing elements, our architecture works at much higher clock frequency (at least 4 times) and reduces area cost about 32% compared with its bit-parallel counterpart. The proposed hardware accelerator can be used in different disciplines from low bit rate to high bit rate by making a tradeoff between the degree of parallelism or using fast algorithm or a combination of both.…”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model by Megat Syahirul Amin, Megat Ali, Azlee, Zabidi, Nooritawati, Md Tahir, Ihsan, Mohd Yassin, Eskandari, Farzad, Azlinda, Saadon, Mohd Nasir, Taib, Abdul Rahim, Ridzuan

“…System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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