A series defining the antiderivative of an nth order differentiable function is defined. This series provides an explicit expression for the second part of the Fundamental Theorem of Calculus and can facilitate the es...
In this paper, two subband implementations of a frequency invariant beamformer (FIB) are studied. In the first structure, the received array signals are split into subbands and an FIB is operated in each of the corres...
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In this paper, two subband implementations of a frequency invariant beamformer (FIB) are studied. In the first structure, the received array signals are split into subbands and an FIB is operated in each of the corresponding decimated subbands, with a potential of achieving a lower computational complexity. As the spatio-temporal distribution of the subband signals is different from the original fullband signal, a modified design method of the FIB is proposed. Based on the subband implementation, we then change the sensor spacings of different subband signals so that lower frequency bands have a larger spacing, which results in a class of FIBs with scaled aperture with improved performance in lower frequencies. Several design examples are given to show the performance of our new structures.
In this contribution, we further examine our previous studies on the nonlinear texture image modelling based on Volterra series. The observed image, which is assumed to be expressed as an output of a two dimensional V...
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In this contribution, we further examine our previous studies on the nonlinear texture image modelling based on Volterra series. The observed image, which is assumed to be expressed as an output of a two dimensional Volterra filter driven by a Gaussian input image, is corrupted by an independent Gaussian random noise. Both of the input image and filter parameters are unknown and hence, the problem can be classified as blind system identification. To estimate the unknown parameters, we formulate the equations that relate the parameters of the image model with the cumulant properties of the observed output image. The solution of the formulated equations which are highly nonlinear, is achieved through minimax type of optimization.
In this work, the idea of cross-layer design for wireless sensor networks is exploited to improve the network performance. We present a new energy efficient cooperative routing scheme with space diversity using space-...
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In this work, the idea of cross-layer design for wireless sensor networks is exploited to improve the network performance. We present a new energy efficient cooperative routing scheme with space diversity using space-time block codes (STBCs) as well as the link quality. In our solution, the selected multiple nodes act as multiple transmitting and receiving antennas. Full diversity from the orthogonal STBC is utilized to overcome multipath fading and to enhance power efficiency. The steady state network performance measures, such as, network throughput and delay are analyzed via Markov chain modelling. Compared with the traditional single relay routing method and the single receiving diversity routing method, our proposed method outperforms the other two in low SNR environments and provides higher throughput and similar delay in high SNR environments.
The problem of texture characterisation is attempted using a two-dimensional (2-D) autoregressive (AR) modelling technique. Each distinct texture is represented by a different set of 2-D AR model coefficients. A metho...
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The problem of texture characterisation is attempted using a two-dimensional (2-D) autoregressive (AR) modelling technique. Each distinct texture is represented by a different set of 2-D AR model coefficients. A method to estimate AR model coefficients is proposed by relating the extended Yule-Walker system of equations in the third-order statistical domain to the same system in the second-order statistical domain using a constrained optimisation formulation. This method is applied to an image with a constant texture in block-by-block process, so that a number of sets of AR model coefficients are obtained. The minimum hierarchical clustering technique and a weighting scheme are then applied to these sets of coefficients, in order to obtain the final estimation.
In this paper, we present the development of a digital image retrieval technique using autocorrelogram and wavelet based texture feature. Autocorrelogram is a color feature that is able to incorporate the spatial corr...
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In this paper, we present the development of a digital image retrieval technique using autocorrelogram and wavelet based texture feature. Autocorrelogram is a color feature that is able to incorporate the spatial correlation of alike color and is tolerant to large changes in appearance, color, contrast, and brightness. A wavelet transform is used to analyze the textures that are characterized by their energy distribution in each sub-band. We propose an integration of the autocorrelogram and wavelet based texture to improve the performance of the image retrieval system. Experimental results suggest that the proposed integration offers much better performance than using the features separately.
The causes of over-expression for many diseases are typically unknown, but current studies show that copy number aberrations may be strong candidates for driving gene overexpression. We present the use of the generali...
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The causes of over-expression for many diseases are typically unknown, but current studies show that copy number aberrations may be strong candidates for driving gene overexpression. We present the use of the generalized singular value decomposition (GSVD) for simultaneously identifying relevant influences common to only copy numbers, gene expression, or both measurements in conjunction. These groups are reported and gene ontology (GO) annotations are used as a functional assessment of the groupings accompanied by probabilistic significance obtained by combinatorics. We illustrate this method for two independently published studies of pancreatic cancer and breast cancer, where public gene expression and DNA copy number data is provided and measured across numerous tumor cell lines.
In VLSI design, crossings of interconnections occupy space and cause delay. In particular, it is desirable to have planar networks for FPGA synthesis and sub-micron LSIs, since delays in the interconnections and cross...
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In VLSI design, crossings of interconnections occupy space and cause delay. In particular, it is desirable to have planar networks for FPGA synthesis and sub-micron LSIs, since delays in the interconnections and crossings are comparable to the delays for logic circuits. Decision diagrams (DDs) provide a simple technology mapping, and planar DDs result in planar networks. In this paper, we present a deterministic method to construct planar Linearly Transformed Binary Decision Diagrams (BDDs) by Walsh transform spectral coefficients.
This work investigates multiple-mode tracking method with node selection using bearings-only measurements. We combine multiple-mode extended Kalman filter with node resource management to conserve energy while trackin...
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This work investigates multiple-mode tracking method with node selection using bearings-only measurements. We combine multiple-mode extended Kalman filter with node resource management to conserve energy while tracking a maneuvering target. Experiments using real data show that the MM adapts quicker to target maneuvers than the realizable single-mode tracker. Additional experiments show that the simplex node selection leads to better geolocation performance compared to the closest node selection when the number of active nodes is set to two.
We generalize a new incoherent wideband direction-of-arrival (DOA) estimation algorithm that provides higher resolution than traditional incoherent techniques. The new method is able to better adjust its beam response...
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We generalize a new incoherent wideband direction-of-arrival (DOA) estimation algorithm that provides higher resolution than traditional incoherent techniques. The new method is able to better adjust its beam response when multiple sources are present than incoherent MUSIC. The original algorithm was designed to work strictly for an uniform linear array. In this paper, we demonstrate how to generalize the algorithm to work over arbitrary 1D or 2D arrays. We demonstrate the higher resolution of the new algorithm against incoherent MUSIC for 1D and 2D arrays using simulations of two source signals.
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