Current Issue : July - September Volume : 2012 Issue Number : 3 Articles : 5 Articles
Spectrum-compatible earthquake time histories have been widely used for seismic analysis and design. In this paper, a data\r\nprocessing method, Hilbert-Huang transform, is applied to generate earthquake time histories compatible with the target seismic\r\ndesign spectra based onmultiple actual earthquake records. Each actual earthquake record is decomposed into several components\r\nof time-dependent amplitude and frequency by Hilbert-Huang transform. The spectrum-compatible earthquake time history is\r\nobtained by solving an optimization problem to minimize the relative difference between the response spectrum of the generated\r\ntime history and the target seismic design spectra. Since the basis for generating spectrum-compatible earthquake time histories\r\nis derived from actual earthquake records by employing the Hilbert-Huang transform, the nonstationary characteristics and the\r\nnatural properties of the seed earthquake records are well preserved in the generated earthquake time histories....
Joint precoder and decoder optimization is considered for uplinkmultiusermultiple-inputmultiple-output (MU-MIMO) systems\r\nwith limited channel state information (CSI) at both the transmitters and receivers. Instead of counting on complex iterativebased\r\nalgorithms, an efficient and noniterative QR-based linear transceiver pair design is employed. In addition, an equal power\r\ndistribution (EPD) scheme is applied to adjust transmit power allocation of each mobile station (MS) between its symbols\r\nunder the total transmit-power constraint. Simulations are conducted to provide a comparative evaluation of the proposed QREPD\r\nalgorithm with other transceiver designs on the sum mean-squared error (SMSE) and the averaged bit-error-rate (BER)\r\nperformance....
Baseband functions like channel estimation and symbol detection of sophisticated telecommunications systems require matrix\r\noperations, which apply highly nonlinear operations like division or square root. In this paper, a scalable low-complexity\r\napproximation method of the inverse square root is developed and applied in Cholesky and QR decompositions. Computation is\r\nderived by exploiting the binary representation of the fixedpoint numbers and by substituting the highly nonlinear inverse square\r\nroot operation with a more implementation appropriate function. Low complexity is obtained since the proposed method does not\r\nuse large multipliers or look-up tables (LUT). Due to the scalability, the approximation accuracy can be adjusted according to the\r\ntargeted application. The method is applied also as an accelerating unit of an application-specific instruction-set processor (ASIP)\r\nand as a software routine of a conventional DSP. As a result, the method can accelerate any fixed-point system where cost-efficiency\r\nand low power consumption are of high importance, and coarse approximation of inverse square root operation is required....
In recent years, automatic visual coral reef monitoring has been proposed to solve the demerits of manual monitoring techniques.\r\nThis paper proposes a novel method to reduce the computational cost of the standard Active Appearance Model (AAM) for\r\nautomatic fish species identification by using an original multiclass AAM. The main novelty is the normalization of speciesspecific\r\nAAMs using techniques tailored to meet with fish species identification. Shape models associated to species-specific AAMs\r\nare automatically normalized by means of linear interpolations and manual correspondences between shapes of different species. It\r\nleads to a Unified Active AppearanceModel built from species that present characteristic texture patterns. Experiments are carried\r\nout on images of fish of four different families. The technique provides correct classification rates up to 92% on 5 species and\r\n84.5% on 12 species and is more than 4 times faster than the standard AAM on 12 species....
We propose to model a tracked object in a video sequence by locating a list of object features that are ranked according to their\r\nability to differentiate against the image background. The Bayesian inference is utilised to derive the probabilistic location of the\r\nobject in the current frame, with the prior being approximated from the previous frame and the posterior achieved via the current\r\npixel distribution of the object. Consideration has also been made to a number of relevant aspects of object tracking including\r\nmultidimensional features and the mixture of colours, textures, and object motion. The experiment of the proposed method on\r\nthe video sequences has been conducted and has shown its effectiveness in capturing the target in a moving background and with\r\nnonrigid object motion....
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