Search results for "VECTOR"
showing 10 items of 2660 documents
Hybrid optical-digital method for local-displacement analysis by use of a phase-space representation.
2010
A method for evaluating the local deformation or displacement of an object in speckle metrology is described. The local displacements of the object in one direction are digitally coded in a one-dimensional specklegram. By optically performing the local spectrum of this pattern, one simultaneously achieves information about the local displacement and its spatial position. The good performance of this technique is demonstrated with computer-generated test signals.
A Support Vector Machine Signal Estimation Framework
2018
Support vector machine (SVM) were originally conceived as efficient methods for pattern recognition and classification, and the SVR was subsequently proposed as the SVM implementation for regression and function approximation. Nowadays, the SVR and other kernel‐based regression methods have become a mature and recognized tool in digital signal processing (DSP). This chapter starts to pave the way to treat all the problems within the field of kernel machines, and presents the fundamentals for a simple, framework for tackling estimation problems in DSP using support vector machine SVM. It outlines the particular models and approximations defined within the framework. The chapter concludes wit…
A novel method for network intrusion detection based on nonlinear SNE and SVM
2017
In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse…
Reduced Reference Mesh Visual Quality Assessment Based on Convolutional Neural Network
2018
3D meshes are usually affected by various visual distortions during their transmission and geometric processing. In this paper we propose a reduced reference method for mesh visual quality assessment. The method compares features extracted from the distorted mesh and the original one using a convolutional neural network in order to estimate the visual quality score. The perceptual distance between two meshes is computed as the Kullback-Leibler divergence between the two sets of feature vectors. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstr…
Dynamics of Vertebral Column Observed by Stereovision and Recurrent Neural Network Model
2005
A new non-invasive method for investigation of movement of selected points on the vertebral column is presented. The registration of position of points marked on patient's body is performed by 4 infrared cameras. This experiment enables to reconstruct 3-dimensional trajectories of displacement of marked points. We introduce recurrent neural networks as formal nonlinear dynamical models of each point trajectory. These models are based only on experimental data and are set up of minimal number of parameters. Therefore they are suitable for pattern recognition problems.
Merging the transform step and the quantization step for Karhunen-Loeve transform based image compression
2000
Transform coding is one of the most important methods for lossy image compression. The optimum linear transform - known as Karhunen-Loeve transform (KLT) - was difficult to implement in the classic way. Now, due to continuous improvements in neural network's performance, the KLT method becomes more topical then ever. We propose a new scheme where the quantization step is merged together with the transform step during the learning phase. The new method is tested for different levels of quantization and for different types of quantizers. Experimental results presented in the paper prove that the new proposed scheme always gives better results than the state-of-the-art solution.
Maximum Displacement Variability of Stochastic Structures Subject to Deterministic Earthquake Loading
1998
The variability of the maximum response displacement of random frame structures under deterministic earthquake loading are examined in this paper using stochastic finite element techniques. The elastic modulus and the mass density are assumed to be described by cross-correlated stochastic fields. Specifically, a variability response function formulation is used for this problem, which allows for calculation of spectral-distribution-free upper bounds of the maximum displacement variance. Further, under the assumption of prespecified correlation functions describing the spatial variation of the material properties, variability response functions are used to calculate the corresponding maximum…
Accuracy of stereotactic coordinate transformation using a localisation frame and computed tomographic imaging
1999
The accuracy of coordinate transformation from a CT image to a stereotactic frame was investigated for stereotactic systems using a localisation frame and matrix-based coordinate transformation. The main source of error influencing calculation was input data, due to inaccurate calculation of the centres of the rods of the localisation frame in the CT image, and the propagation of this input error during subsequent matrix calculation. Systemic errors during matrix calculation do not exist, and rounding off errors were of subordinate importance compared to the input data error. The influence of input data error on coordinate transformation was studied by geometric methods, computer simulation…
IMPROVING CNC MACHINE TOOLS ACCURACY USING MODELING AND COMPUTER SIMULATION TECHNIQUES
2007
Abstract The position was one of the first parameters that required the introduction of automatic control process. One of the most representative applications is represented by the feed drives of the computer numerically controlled (CNC) machine tools. Today, it is possible to use computer simulation techniques in analysing and synthesising position control systems. Thus, the behaviour of the CNC machine tools feed drives can be treated much more realistically. It is the purpose of this paper to show how simulation can be used to accurately represent, predict and improve the performance of a CNC machine tool feed servo drives.
Frequency Regulation of Hybrid Power System by Optimized Adaptive Fuzzy PID Controller
2020
In this study, an adaptive fuzzy PID (AFPID) regulator has been proposed for frequency control of hybrid power system. For controller parameter optimization, an upgraded Whale Optimization Algorithm (WOA) has been employed. In the proposed Upgraded WOA (UWOA) technique, a cosine function is incorporated in the original WOA for determining control parameter to manage the position of whales throughout optimization procedure. Furthermore, scaling factors are employed in original WOA to adjust the travel of whales in search procedure. Proposed UWOA technique is employed to design an AFPID controller for frequency regulation of a hybrid power system It is demonstrated that UWOA technique out per…