In this study, the authors propose a low-complexity frequency-domain turbo equalisation scheme for doubly-selective high-frequency (HF) channel. The performance of time- and frequency-domain turbo equalisers (TD/FD-TE...
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In this study, the authors propose a low-complexity frequency-domain turbo equalisation scheme for doubly-selective high-frequency (HF) channel. The performance of time- and frequency-domain turbo equalisers (TD/FD-TE) by applying them to the waveforms of STANAG 4539 is compared. Compared with TD-TE, FD-TE has reduced computational complexity. However, its performance degrades for time-varying channels. To improve the performance of FD-TE, they divide the received blocks into consecutive sub-blocks where the channel impulse response remains fixed for each sub-block. Due to the absence of cyclic prefix in the sub-blocks, the overlap frequency-domain equalisation (FDE) is used in the first iteration. In the following iterations, the authors remove the interference term, therefore the channel matrix becomes circular and low-complexity FDE is used. Simulation results show that compared with the TD-TE, the performance loss of FD-TE equipped with the authors' proposed scheme at the bit error rate of 1x10(-5) is <1dB with much lower computational complexity. By real-time software defined radio (SDR) implementation of the proposed receiver on a general purpose processor (GPP), the authors ensure real-time feasibility of their algorithm. They use GNU radio tool for SDR implementation. It is shown that with GNU radio capabilities such as multi-threading and pipelining, further reduction in processing time can be achieved.
We present various complexity results for scheduling unit-time jobs subject to OR-precedence constraints. We prove that minimizing the total weighted completion time is strongly NP-hard,even on a single machine. In co...
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We present various complexity results for scheduling unit-time jobs subject to OR-precedence constraints. We prove that minimizing the total weighted completion time is strongly NP-hard,even on a single machine. In contrast, we give a polynomial-time algorithm for minimizing the makespan and the total completion time on identical. parallel machines. (c) 2004 Elsevier B.V. All rights reserved.
Image restoration is formulated using a truncated singular-value-decomposition (SVD) filter bank. A pair of known data patterns is used for identifying a small convolution operator. This is achieved by matrix pseudo-i...
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Image restoration is formulated using a truncated singular-value-decomposition (SVD) filter bank. A pair of known data patterns is used for identifying a small convolution operator. This is achieved by matrix pseudo-inversion based on SVD. Unlike conventional approaches, however, here SVD is performed upon a data-pattern matrix that is much smaller than the image size, leading to an enormous saving in computation. Regularisation is realised by first decomposing the operator into a bank of sub-filters, and then discarding some high-order ones to avoid noise amplification. By estimating the noise spectrum, sub-filters that produce noise energy more than that of useful information are abandoned. Therefore high-order components in the spectrum responsible for noise amplification are rejected. With the obtained small kernel, image restoration is implemented by convolution in the space domain. Numerical results are given to show the effectiveness of the proposed technique.
Adjoint-based error estimation and grid adaptive procedures are investigated for their robustness and effectiveness in improving the accuracy of functional outputs such as lift and drag. The adjoint error estimates re...
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Adjoint-based error estimation and grid adaptive procedures are investigated for their robustness and effectiveness in improving the accuracy of functional outputs such as lift and drag. The adjoint error estimates relate the global error in the output function to the local residual errors in the flow solution via adjoint variables as weight functions. These error estimates are used as a correction to produce improved functional estimates. Based on this error correction procedure, two output-based grid adaptive approaches are implemented and compared. While both approaches strive to improve the accuracy of the computed output, the means by which the adaptation parameters are formed differ. The first approach strives to improve the computable error estimates by forming adaptation parameters based on the level of error in the computable error estimates. The second approach uses the computable error estimates as adaptation parameters. Grid adaptation is performed with h-refinement and results are presented for two-dimensional, inviscid, incompressible flows. (C) 2008 Elsevier Ltd. All rights reserved.
Multiscale convexity analysis of certain fractal binary objects-like 8-segment Koch quadric, Koch triadic, and random Koch quadric and triadic islands-is performed via (i) morphologic openings with respect to recursiv...
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Multiscale convexity analysis of certain fractal binary objects-like 8-segment Koch quadric, Koch triadic, and random Koch quadric and triadic islands-is performed via (i) morphologic openings with respect to recursively changing the size of a template. and (ii) construction of convex hulls through half-plane closings. Based on scale vs convexity measure relationship, transition levels between the morphologic regimes are determined as crossover scales. These crossover scales are taken as the basis to segment binary fractal objects into various morphologically prominent zones. Each segmented zone is characterized through normalized morphologic complexity measures. Despite the fact that there is no notably significant relationship between the zone-wise complexity measures and fractal dimensions computed by conventional box counting method, fractal objects-whether they are generated deterministically or by introducing randomness-possess morphologically significant sub-zones with varied degrees of spatial complexities. Classification of realistic fractal sets and/or fields according to sub-zones possessing varied degrees of spatial complexities provides insight to explore links with the physical processes involved in the formation of fractal-like phenomena. (C) 2008 Elsevier Ltd. All rights reserved.
In this paper we study the query complexity of finding local minimum points of a boolean function. This task occurs frequently in exact learning algorithms for many natural classes, such as monotone DNF. O(log n)-term...
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In this paper we study the query complexity of finding local minimum points of a boolean function. This task occurs frequently in exact learning algorithms for many natural classes, such as monotone DNF. O(log n)-term DNF, unate DNF, and decision trees. On the negative side, we prove that any (possibly randomized) algorithm that produces a local minimum of a function f chosen from a sufficiently "rich" concept class, using a membership oracle for f, must ask Omega (n(2)) membership queries in the worst case. In particular, this lower bound applies to the class of decision trees. A simple algorithm is known that achieves this lower bound. On the positive side, we show that for the class O(log n)-term DNF finding local minimum points requires only Theta (n log n) membership queries (and more generally Theta (tn) membership queries for t-term. DNF with t less than or equal to n). This efficient procedure improves the time and query complexity of known learning algorithms for the class O (log n)-term DNF. (C) 2001 Elsevier Science.
Pattern division multiple access (PDMA) is a promising non-orthogonal multiple access technology for the next generation wireless communication systems. In PDMA systems, the inherent residual transceiver impairments i...
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Pattern division multiple access (PDMA) is a promising non-orthogonal multiple access technology for the next generation wireless communication systems. In PDMA systems, the inherent residual transceiver impairments introduced by nonideal hardwares incur significant performance degradation. In this paper, we propose a residual-transceiver-impairments-aware (RTIA) expectation propagation algorithm (EPA) receiver to mitigate the detrimental influences of the nonideal hardware imperfections for uplink PDMA systems. The user-specific transmitter distortion powers are considered in the message passing procedure of the EPA detection. The parallel interference cancellation (PIC) scheme is incorporated into the proposed RTIA-EPA receiver to further improve the system performance and reduce the computational complexity. Simulation results illustrate that the proposed RTIA-EPA and RTIA-EPA-PIC receivers achieve significant performance gains over the conventional residual-transceiver-impairments-agnostic counterparts with negligible computational complexity overhead.
In this paper a new upward separation technique is developed. It is applied to prove that for a class of functions F a separation DTIME(F) not equal NTIME(F) can be characterized by the existence of (not only polynomi...
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In this paper a new upward separation technique is developed. It is applied to prove that for a class of functions F a separation DTIME(F) not equal NTIME(F) can be characterized by the existence of (not only polynomially) sparse sets in certain complexity classes. As a consequence, a solution of an open question of J. Hartmanis (1983, Inform. Process. Lett, 16, 55-60) is obtained: There is an n(O(log n))-sparse set in NP-P iff boolean OR (c >1) NTIME (2(2c rootn)) not equal boolean OR (c >1) DTIME (2(c rootn)) Further he prove that there is an n0 109'1-sparse set in NP - coNP iff boolean OR (c >1) NTIME (2(c rootn)) not equal boolean OR coNTIME (2(c rootn)). The technique also allows us to characterize the existence of sets of different densities in NP - P by the existence of slightly denser sets in NTIME(F) - DTIME(F) for certain classes of functions F. For example, there is an n(O(log) (n))-sparse set in NP - P iff there is an n(O((log n)3))-sparse set in boolean OR (c >1) NTIME (n(c) (log n)) - boolean OR (c >1) DTIME (n(c log n)). The end of the paper is devoted to limitations of the technique. (C) 2001 Academic Press.
The Fruit-fly optimization algorithm (FOA) is good at parallel search ability in the evolution process, but it traps in local optimum sometimes. Simulated Annealing (SA) algorithm accepts the second-optimum solution w...
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The Fruit-fly optimization algorithm (FOA) is good at parallel search ability in the evolution process, but it traps in local optimum sometimes. Simulated Annealing (SA) algorithm accepts the second-optimum solution with Mrtropolis criterion so as to jump out of the local optimum. So, combined the advantages of two algorithms, modified FOA (FOA-SA) algorithm is presented in this paper. In FOA-SA, the smell concentration function is improved as well, so as to get the whole searching directions for fruit-fly. At the same time, in order to solve the problem of the computational complexity in image 2D sparse decomposition, image 1D orthogonal matching pursuit (OMP) algorithm with FOA-SA algorithm is implemented. Experimental results show that the convergence of FOA-SA is better than that in FOA, and the speed of image 1D sparse algorithm is 2.41 times faster than 2D for the 512 x 512 image under the same conditions.
This paper studies for various natural problems in NP whether they can be reduced to sets with low information content, such as branches, P-selective sets, and membership comparable sets. The problems that are studied...
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This paper studies for various natural problems in NP whether they can be reduced to sets with low information content, such as branches, P-selective sets, and membership comparable sets. The problems that are studied include the satisfiability problem, the graph automorphism problem, the undirected graph accessibility problem, the determinant function, and all logspace self-reducible languages. Some of these are complete for complexity classes within NP, but for others an exact complexity theoretic characterization is not known. Reducibility of these problems is studied in a general framework introduced in this paper: prover-verifier protocols with low-complexity provers. It is shown that all these natural problems indeed have such protocols. This fact is used to show, for certain reduction types, that these problems are not reducible to sets with low information content unless their complexity is much less than what it is currently believed to be. The general framework is also used to obtain a new characterization of the complexity class L : L is the class of all logspace self-reducible sets in L (C) 2004 Elsevier Inc. All rights reserved.
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