166 resultados para Vector Auto Regression
Resumo:
Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.
Resumo:
In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.
Resumo:
This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.
Resumo:
Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate Processor performance to micro-architecture parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike's information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques.
Resumo:
The problem of narrowband CFAR (constant false alarm rate) detection of an acoustic source at an unknown location in a range-independent shallow ocean is considered. If a target is present, the received signal vector at an array of N sensors belongs to an M-dimensional subspace if N exceeds the number of propagating modes M in the ocean. A subspace detection method which utilises the knowledge of the signal subspace to enhance the detector performance is presented in thisMpaper. It is shown that, for a given number of sensors N, the performance of a detector using a vector sensor array is significantly better than that using a scalar sensor array. If a target is detected, the detector using a vector sensor array also provides a concurrent coarse estimate of the bearing of the target.
Resumo:
A novel, cost effective,environment-friendly and energetically beneficial alternative method for the synthesis of giant dielectric pseudo-perovskite material CaCu3Ti4O12 (CCTO) is presented. The method involved auto-combustion of an aqueous precursor solution in oxygen atmosphere with the help of external fuels and is capable of producing high amount of CCTO at ultra-low temperature, in the combustion residue itself. The amount of phase generated was observed to be highly dependent on the combustion process i.e. on the nature and amount of external-fuels added for combustion. Two successful fuel combinations capable of producing reasonably higher amount of the desired compound were investigated. On a structural characterization grain size was observed to decrease drastically to nano-dimension compared to submicron-size that was obtained in a traditional sol-gel combustion and subsequent cacination method. Therefore, the method reported can produce nano-crystalline CaCu3Ti4O12 ceramic matrix at an ultra-low temperature and is expected to be applicable for other multifunctional perovskite oxide materials.
Resumo:
The isoscalar axial-vector renormalization constant is reevaluated using the QCD sum-rule method. It is found to be substantially different from the anomaly-free octet axial-vector u¯γμγ5+d¯γμγ5-2s¯γμγ5 coupling. Combining this determination with the known values of the isovector coupling GA and the F/D ratio for the octet current, we find the integral of the polarized proton structure function to be Gp=Fgp1(x)dx=0.135, in agreement with recent measurement by the European Muon Collaboration.
Resumo:
PMSM drive with high dynamic response is the attractive solution for servo applications like robotics, machine tools, electric vehicles. Vector control is widely accepted control strategy for PMSM control, which enables decoupled control of torque and flux, this improving the transient response of torque and speed. As the vector control demands exhaustive real time computations, so the present work is implemented using TI DSP 320C240. Presently position and speed controller have been successfully tested. The feedback information used is shaft (rotor) position from the incremental encoder and two motor currents. We conclude with the hope to extend the present experimental set up for further research related to PMSM applications.
Resumo:
Mandelstam�s argument that PCAC follows from assigning Lorentz quantum numberM=1 to the massless pion is examined in the context of multiparticle dual resonance model. We construct a factorisable dual model for pions which is formulated operatorially on the harmonic oscillator Fock space along the lines of Neveu-Schwarz model. The model has bothm ? andm ? as arbitrary parameters unconstrained by the duality requirement. Adler self-consistency condition is satisfied if and only if the conditionm?2?m?2=1/2 is imposed, in which case the model reduces to the chiral dual pion model of Neveu and Thorn, and Schwarz. The Lorentz quantum number of the pion in the dual model is shown to beM=0.
Resumo:
A microscopic expression for the frequency and wave vector dependent dielectric constant of a dense dipolar liquid is derived starting from the linear response theory. The new expression properly takes into account the effects of the translational modes in the polarization relaxation. The longitudinal and the transverse components of the dielectric constant show vastly different behavior at the intermediate values of the wave vector k. We find that the microscopic structure of the dense liquid plays an important role at intermediate wave vectors. The continuum model description of the dielectric constant, although appropriate at very small values of wave vector, breaks down completely at the intermediate values of k. Numerical results for the longitudinal and the transverse dielectric constants are obtained by using the direct correlation function from the mean‐spherical approximation for dipolar hard spheres. We show that our results are consistent with all the limiting expressions known for the dielectric function of matter.
Resumo:
A numerical integration procedure for rotational motion using a rotation vector parametrization is explored from an engineering perspective by using rudimentary vector analysis. The incremental rotation vector, angular velocity and acceleration correspond to different tangent spaces of the rotation manifold at different times and have a non-vectorial character. We rewrite the equation of motion in terms of vectors lying in the same tangent space, facilitating vector space operations consistent with the underlying geometric structure. While any integration algorithm (that works within a vector space setting) may be used, we presently employ a family of explicit Runge-Kutta algorithms to solve this equation. While this work is primarily motivated out of a need for highly accurate numerical solutions of dissipative rotational systems of engineering interest, we also compare the numerical performance of the present scheme with some of the invariant preserving schemes, namely ALGO-C1, STW, LIEMIDEA] and SUBCYC-M. Numerical results show better local accuracy via the present approach vis-a-vis the preserving algorithms. It is also noted that the preserving algorithms do not simultaneously preserve all constants of motion. We incorporate adaptive time-stepping within the present scheme and this in turn enables still higher accuracy and a `near preservation' of constants of motion over significantly longer intervals. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Resumo:
The complex three-dimensional flowfield produced by secondary injection of hot gases in a rocket nozzle for thrust vector control is analyzed by solving unsteady three-dimensional Euler equations with appropriate boundary conditions. Various system performance parameters like secondary jet amplification factor and axial thrust augmentation are deduced by integrating the nozzle wall pressure distributions obtained as part of the flowfield solution and compared with measurements taken in actual static tests. The agreement is good within the practical range of secondary injectant flow rates for thrust vector control applications.
Resumo:
This paper presents an optimization algorithm for an ammonia reactor based on a regression model relating the yield to several parameters, control inputs and disturbances. This model is derived from the data generated by hybrid simulation of the steady-state equations describing the reactor behaviour. The simplicity of the optimization program along with its ability to take into account constraints on flow variables make it best suited in supervisory control applications.
Resumo:
Genetic transformation systems have been established for Brassica nigra (cv. IC 257) by using an Agrobacterium binary vector as well as by direct DNA uptake of a plasmid vector. Both the type of vectors carried nptII gene and gus gene. For Agrobacterium mediated transformation, hypocotyl tissue explants were used, and up to 33% of the explants produced calli on selection medium. All of these expressed B-glucuronidase gene on histochemical staining. Protoplasts isolated from hypocotyl tissues of seedlings could be transformed with a plasmid vector by FEG mediated uptake of vector DNA. A number of fertile kanamycin resistant plants were obtained using both the methods, and their transformed nature was confirmed by Southern blot analysis and histochemical staining for GUS. Backcrossed and selfed progenies of these transformed plants showed the presence of npt and gus genes.