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Multidimensional (nD) Systems (nDs), 2011 7th International Workshop on

Date 5-7 Sept. 2011

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  • Welcome

    Publication Year: 2011 , Page(s): 1 - 3
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  • Sponsors

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  • Call for papers

    Publication Year: 2011 , Page(s): 1
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  • Table of contents

    Publication Year: 2011 , Page(s): i - iv
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  • Committees

    Publication Year: 2011 , Page(s): 1
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  • Recent progress on analog/digital VLSI 2D filter circuits for beamforming antenna arrays

    Publication Year: 2011 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2344 KB) |  | HTML iconHTML  

    This paper presents three recently proposed 2D filter architectures suitable for UWB beamforming of spatio-temporal plane waves. Massively-parallel systolic array based hardware architectures for the reduced complexity direct-form-I and the differential-form 2D multi-beam filters that operate in discrete-space-discrete-time domain are presented. Magnitude frequency response obtained by prototype FPGA implementation on Xilinx Virtex-4 Sx35-10ff668 device for dual-beam case with space-space DOAs 10° and 70° is presented. A novel 2D fan filter architecture that operates in discrete-space-continuous-time (DSCT) mixed domain is also presented. An all-pass filter based time delay approximation is used to obtain the DSCT version of the available 2D FIR digital fan filter prototype. The proposed time delay approximation method is simulated using the BSIM4 models of 90 nm CMOS from ST Microelectronics using Cadence Virtuoso. The 2D fan filter magnitude frequency response is obtained from both theoretical and simulated data for the all-pass time delay approximation. View full abstract»

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  • Discrete-space continuous-time analog circuits for spatially-bandpass 2D IIR beam filters

    Publication Year: 2011 , Page(s): 1 - 7
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1047 KB) |  | HTML iconHTML  

    Discrete-space continuous-time analog circuits and signal flow graphs (SFGs) for the spatially-bandpass 2D IIR beam filters are proposed for implementing broadband beamforming of temporally down-converted RF signals. The proposed filters have mixed domain 2D transfer-functions with potential applications in wireless communications, cognitive radio, radar and radio-astronomy. The proposed circuit has been verified for correct functionality by simulating in Cadence Virtuoso. These analog filters have advantages over its digital counterparts such as the need for temporal over-sampling, temporal-aliasing, A/D converters are avoided which as a result makes the filters free from quantization noise and reduces the power dissipation due to switching leading to potential lower power circuits. View full abstract»

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  • Modelling of wideband inter-element EM coupling in 2D space-time frequency domain

    Publication Year: 2011 , Page(s): 1 - 7
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (194 KB) |  | HTML iconHTML  

    Wideband antenna arrays having elements spaced in a uniformly-spaced configuration are increasingly common in electromagnetic (EM) beamformers for radio-astronomy, pulsar science, radar, and wireless communications. EM coupling between elements cause changes to the polar pattern and lead to increased noise in the system. Traditionally, scattering (S) parameters are used to measure of coupling. However, S-parameter measurements by themselves do not lead to a complete view of the effects of coupling. In this work, the EM coupling is modelled as a 2D space-time phenomena using well-established theory in the multi-dimensional signal processing area. Measured S-parameters obtained from a vector network analyzer (VNA) can be used for de-embedding coupling effects from measured beamformer performance. Here, an overview of the proposed method is provided, followed by closed-form equations that express EM coupling between neighbouring elements in an array in terms of S-parameters and reflection coefficients. The proposed equations are verified using A) FEKO for EM simulations and B) Agilent's Advanced Design System (ADS) for S-parameter simulations. Both software models are found to agreewith the proposed equations, thereby confirming their validity at the simulation level. Experimental verification is left for future work. View full abstract»

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  • Towards an adaptive minimum variance control scheme for specimen drift compensation in transmission electron microscopes

    Publication Year: 2011 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (382 KB) |  | HTML iconHTML  

    Transmission electron microscopes are the tools of choice in materials science, semiconductor, and biological research and it is expected that they will be increasingly used to autonomously perform high-volume, repetitive, nano-measurements in the near future. Thus, there is a clear need to develop automation strategies for these microscopes. This paper introduces an adaptive minimum variance control scheme to compensate specimen drift, a common cause of image blurring in long-exposure images. The controller, which is new in the electron microscope literature, makes use of ARMASA, a statistical toolbox designed to identify linear models from finite-length data sets, to generate ARMA models of the drift process `on-the-fly'. These models are then used as part of a controller designed to reduce the drift variance. The benefits of the proposed scheme, which can be quite substantial, are illustrated through a set of simulations that use a model of the drift present in a sequence of experimental images. View full abstract»

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  • Multisensor data fusion for advanced driver assistance systems - the Active Safety Car project

    Publication Year: 2011 , Page(s): 1 - 5
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2127 KB) |  | HTML iconHTML  

    Driver assistance systems support overstrained and affected drivers and become more and more essential for series-production vehicles. Object detection and segmentation is one of the most challenging research topics in this field. In order to warn the driver or automatically break before a potential collision, objects intersecting the path of the host vehicle have to be detected and classified. Most recently developed approaches are based on two dimensional image processing, sometimes in combination with a tracking algorithm associating detections in consecutive frames to one and the same object. Further robustness is achieved by multisensor data fusion, i.e. information by two or more different sensors (e.g. camera and radar data) are fused in order to get a much more reliable result. Another aspect for safety applications is communication between cars, which provides additional sensor locations and thus also requires data fusion technology. Two different approaches for data fusion are proposed and first results are presented. View full abstract»

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  • On multidimensional velocity filter banks for video-based motion analysis of world-coordinate objects

    Publication Year: 2011 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (875 KB) |  | HTML iconHTML  

    Linear multidimensional filter theory provides an elegant way to analyse movement within image sequences, i.e. to separate objects moving in different directions or at different speeds. Due to its time-invariant transfer function a single filter is restricted to specific motions, for which reason a consecutively parameterized filter bank is needed to differentiate a broader set of movement. In this paper, an introduction to velocity filtering is given and unwanted side-effects are discussed, i.e. spatio-temporal ringing and perspective distortion. As a practical example a traffic scene is analysed by means of inverse perspective mapping followed by a velocity filter bank. View full abstract»

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  • Detection and estimation translations of large images using random projections

    Publication Year: 2011 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (118 KB) |  | HTML iconHTML  

    This paper describes a technique of fast detection and estimation of translations in large image frames for image stabilization. Our approach is based on random projection methodology for reduction of image dimension which retain with prescribed accuracy and probability the squared Euclidean norm of projected vectors (image's rows and columns). We formulate simple optimization problems for estimation of vertical and horizontal motions of the frame. The first one tries to find the best match between energies (squared norms) of rows (columns) of the actual projected image and the projected reference frame. The second one uses the squared Euclidean distance between the same objects. An iterative procedure based on the successive, alternate estimation of a vertical and a horizontal translation is proposed. View full abstract»

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  • SOS-based H control of 2-D polynomial FMLSS model

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (335 KB) |  | HTML iconHTML  

    1-D polynomial systems become more and more popular in respect that the systems are generalization of conventional 1-D linear systems and can represent nonlinear control systems effectively. Based on the same consideration, conventional 2-D Fornasini Marchesini local state space (FMLSS) models are extended to 2-D polynomial FMLSS model in this paper, with the elements of the system matrices are polynomial. The problems of stability analysis and H control for the 2-D polynomial FMLSS model are considered: a sufficient condition for stability of 2-D polynomial FMLSS model is proposed and a polynomial H controller is obtained in terms of sum of squares (SOS). An example is provided to show the effectiveness of the approach. View full abstract»

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  • Analytical sub-band filtering technique of Two-Dimensional adaptive Notch Filter

    Publication Year: 2011 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2732 KB) |  | HTML iconHTML  

    A Two-Dimensional (2-D) Notch Filter is typically used for removing sinusoidal interferences from the a 2-D broadband image. An adaptive algorithm is subsequently applied to the filters in order to provide more flexibility to cope with multiple unknown interferences. Later on, a sub-band filtering technique is introduced to achieve decent convergence times. This work mainly focuses on an analysis of sub-band filtering methods. On previous work, a conventional 2-D FIR filter is used and the number of sub-band is not clearly recommended. Therefore, this work aims to provide other alternative methods of sub-band filtering and to clarify the issues related to the number of sub-bands. The simulation results is also presented including analysis of each method. View full abstract»

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  • Adaptive beamforming by simultaneous projection in dual domains

    Publication Year: 2011 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (611 KB) |  | HTML iconHTML  

    In this paper, we propose an efficient adaptive beamforming algorithm based on the simultaneous projection in dual domains. In the (primary) domain of beamformer weights, the proposed algorithm operates the projections onto multiple closed convex sets each of which bounds the magnitude of an instantaneous beamformer-output. At the same time, it also operates the projection onto a closed ball in a secondary domain. All the projections are combined convexly in the primary domain. The idea of the secondary-domain projection is to bound the energy of interfering signals remaining in the beamformer output. The numerical examples show that the proposed algorithm achieves drastic improvements of the convergence speed. View full abstract»

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  • Asymptotic unknown input observers for two-dimensional systems

    Publication Year: 2011 , Page(s): 1 - 5
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (129 KB) |  | HTML iconHTML  

    This paper is concerned with asymptotic unknown input observers (UIOs) for two-dimensional (2-D) systems. A sufficient condition for the existence of the asymptotic UIO is given in terms of the rank conditions of the given system matrices. Based on this condition, a simple and effective method for designing asymptotic UIOs for 2-D systems is given. An example is also presented to illustrate the proposed design method. View full abstract»

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  • Music emotion recognition with consideration of personal preference

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (327 KB) |  | HTML iconHTML  

    In order to discover the relationship between music and the emotion that it may evoke, twenty-one features have been extracted to describe music. A feature selection algorithm called sequential floating forward selection (SFFS) is utilized to find discriminative features. An estimation of the correlation coefficient was applied to determine features of music that evoke an emotion. These features were then used to train two support vector machines (SVMs) for an individual subject to classify music that evokes happiness, anger, sadness, and peacefulness. Experimental results show that the proposed approach can be used to classify music that evokes an emotion for an individual subject with high classification accuracy. View full abstract»

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  • Object-based rendering and 3D reconstruction using a moveable image-based rendering system

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (636 KB) |  | HTML iconHTML  

    Image-based rendering (IBR) is a promising technology for rendering photo-realistic views of scenes from a collection of densely sampled images or videos, and for developing revolutionary immersive viewing systems. However, most multiple camera systems are designed to be stationary and hence their ability to cope with moving objects and dynamic environment is somewhat limited. This paper studies the design and development of a movable IBR (M-IBR) system for object-based rendering and 3D reconstruction in large environment. To reduce shaky motion due to the movable system, we develop video stabilization algorithm based on scale invariant feature transformation. Also, we propose a new segmentation-based mutual-information matching algorithm to estimate the dense depth maps and preserve discontinuities for better quality of rendering. Using these depth maps and sequential structure from motion technique, we estimate the location of the M-IBR system to obtain a set of fairly reliable 3D point cloud. After detecting and removing possible outliers using Kalman-based tracking, we propose a new robust RBF-based modeling of the 3D surfaces to recover high quality 3D geometry. The effectiveness of the proposed system and algorithms is demonstrated using multi-view videos in an open environment. View full abstract»

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  • Compressed sensing MRI by two-dimensional wavelet filter banks

    Publication Year: 2011 , Page(s): 1 - 6
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (587 KB) |  | HTML iconHTML  

    How to speed up the scanning process is the bottleneck problem of magnetic resonance imaging (MRI). As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) provides a solution to this problem because of its potential of reconstructing MR images from fewer samples. Recent work has demonstrated successful application of CS to MRI. However, the frequently used sparsifying transform is the traditional discrete wavelet transform, which has shortcomings, such as oscillations, lack of directionality and shift variance. This paper implements compressed sensing MRI reconstruction based on a new kind of two-dimensional wavelet filter banks which has improved directional selectivity and approximate shift invariance. Our experiments show that the method can significantly reduce aliasing and achieve higher peak signal to noise ratio (PSNR). View full abstract»

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  • A sparse voxel selection approach for fMRI data analysis with multi-dimensional derivative constraints

    Publication Year: 2011 , Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (355 KB) |  | HTML iconHTML  

    Voxel selection techniques can reveal important brain regions in 3-dimensional functional magnetic resonance imaging (fMRI) data analysis. In order to counteract the contamination of noise and find meaningful voxels for fMRI analysis, the sparse representation methods like Lasso have been recently proved to be efficient for voxel selection in fMRI data. However, the voxels selected by these methods generally lose the clustering property of activated brain regions. In this work, we consider a sparse representation approach with multi-dimensional derivative constraints to detect a small portion of fMRI voxels with task relevant information. The proposed method takes into account the correlation and smoothness of activation amplitudes among neighboring voxels in cortex. Preliminary data analysis results validate the effectiveness of the proposed method. View full abstract»

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  • All-pass based IIR multiple notch filter design using Gröbner Basis

    Publication Year: 2011 , Page(s): 1 - 6
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (147 KB) |  | HTML iconHTML  

    In this paper, the digital IIR multiple notch filter based on an all-pass filter design of order 2N is considered. The most important step is about the calculation of the exact notch frequencies. The previous method requires solving of non-linear polynomial equation system which can be difficult to tackle especially for the case with higher number of notch frequencies. The analytical result was derived only for the case of N = 2 not for N = 3 and higher, then the main idea proposed in this paper is focused on solving of the non-linear systems for the cases of higher number of notch frequencies, e.g. N ≥ 3, by employing “Gröbner Basis” theory which has ability to solve multi-variance polynomial equation systems by using the benefit of “lexicographical orderings” in the polynomial rings to make those systems to be “triangular systems” which can be solved by backward substitution. Although the proposed filter design is a one dimensional but the proposed technique involved multi-variance polynomials. Another advantage is that the Gröbner Basis provides symbolic solutions which allow further optimization to satisfy additional constraints such as having minimum group delay. View full abstract»

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  • On selection of spatial-varying regularization parameters in total variation image restoration

    Publication Year: 2011 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (690 KB) |  | HTML iconHTML  

    In this paper, we consider and study total variation (TV) image restoration. The main aim of this paper is to develop a fast TV image restoration method with an automatic selection of spatial-varying regularization parameter scheme to restore blurred and noisy images. The method exploits the generalized cross-validation (GCV) technique to determine inexpensively how much regularization used in each region of an image and in each restoration step. By updating the regularization parameter in each iteration, the restored image can be obtained. Our experimental results show that the visual quality of restored images by the proposed method is very good even without prior knowledge of the original image. We will demonstrate the proposed method is also very efficient. View full abstract»

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  • Design of robust iterative learning control schemes in a finite frequency range

    Publication Year: 2011 , Page(s): 1 - 6
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (218 KB) |  | HTML iconHTML  

    Iterative learning control has been especially developed for systems defined over a finite duration that repeat the same task. Each execution is known as a trial, or pass, and the sequence of operations is that a trial is completed, the system is then reset to the starting location, and the next pass begins. The novel feature of this control law design method is to use information from the previous pass, or a finite number of previous passes, to update the control input applied on the next pass and thereby improve performance from pass-to-pass. Iterative learning control has an inherent two-dimensional systems structure since the dynamics evolve in two independent directions. In this paper, the repetitive process structure is exploited to develop a controller design algorithm that produces both a stabilizing feedback controller in the time domain and a feedforward controller that guarantees convergence in the pass-to-pass domain for all admissible uncertainties. Using the Generalized Kalman-Yakubovich-Popov lemma, controller design is performed over a finite frequency range. A major advantage of this new algorithm lies in the fact that it can be computed using linear matrix inequality software without incurring unacceptable computing cost. View full abstract»

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  • Norm-optimal control of time-varying discrete repetitive processes with iteration-varying reference inputs

    Publication Year: 2011 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (585 KB) |  | HTML iconHTML  

    This paper extends the norm-optimal control design methodology of iterative learning control (ILC) to the case of linear time-varying discrete repetitive processes (LTV-DRP) driven by known iteration-varying reference input signals. Our approach exploits the idea of the internal model principle for robust servomechanism design and uses a state-space model of LTV-DRPs introduced in our earlier work. A general state-feedback solution to the problem is derived that contains as special cases the solutions for time-invariant DRPs and iteration-invariant reference signals as well as the equivalent solutions for the ILC case. A numerical example illustrates the results. View full abstract»

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  • H filtering for a class of 2-D discrete-time parameter-varying systems

    Publication Year: 2011 , Page(s): 1 - 7
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (183 KB) |  | HTML iconHTML  

    This paper deals with H filtering for two-dimensional (2-D) discrete-time linear parameter-varying systems described by the Fornasini-Marchesini second model with matrices that depend rationally on convex-bounded time-varying parameters. A method is proposed for the design of robust 2-D filters with a prescribed H performance for all admissible parameters' trajectories. The filter design method builds on a difference-algebraic representation of the underlying system and is based on a parameter-dependent Lyapunov function with affine dependence on the system parameters. The filtering method is then adapted for designing gain-scheduled (parameter-varying) H filters. The proposed filter designs are tailored via linear matrix inequalities. A numerical example illustrates the potentials of the filtering methods. View full abstract»

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