To solve the schema deception and premature convergence problem in the pure genetic algorithm, based on the theory method of interval, Banach fixpoint and genetic algorithms, the contractive-mapping-hybrid-genetic alg...
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To solve the schema deception and premature convergence problem in the pure genetic algorithm, based on the theory method of interval, Banach fixpoint and genetic algorithms, the contractive-mapping-hybrid-genetic algorithms (CMGA) were constructed and quadratic extension of Lipschitz was applied to testify the multi mode function extremum. The calculating examples validated the algorithmpsilas excellent performance in the global optimization problem The verifying terms are simple and easy to be actualized. The algorithms speed up the convergence obviously and improved reliability, thus the schema deception and premature convergence problem can be well solved.
As the explosive growth of wireless date requirements, heterogeneous network(HetN et) has become an effective solution for improving the system performance such as the throughput. The femtocells are always arranged to...
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As the explosive growth of wireless date requirements, heterogeneous network(HetN et) has become an effective solution for improving the system performance such as the throughput. The femtocells are always arranged to share the spectrum with the macro base stations(MBSs). Thus, the cochannel interference leads to the degradation of the HetN et throughput. In this paper, we discuss the program of spectrum reuse in the two-tier Het Net, and the problem is defined as a Stackelberg game approach. The MBS is play as a leader and it releases a part of spectrum resource for femtocells to avoid intertier interference. And the femtocells provide services to fractional macro users(MUEs) in return. Therefore, the throughput can be improved by the reduction of the inter-tier interference. Compared with the former works, the prominent characteristic of the method in the paper is that the benefit relation between the leader and followers is not measured by the real money. Furthermore, considering the system throughput specifically, we define the utility of the femto base stations(FBSs) by the average throughput as same as the utility of the MBS, which is used to improve the overall throughput of the system. Moreover, the gradient descent algorithm is also applied to compute the Nash equilibrium as the range of variables become continuous. The simulation results indicate that the proposed algorithm can observably reduce the interference and enhance the throughput of the network.
In this paper, an iterative soft multiuser detection (MUD) algorithm is proposed for multiple-input multiple-output multi-carrier code-division multiple access (MIMO MC-CDMA) systems. Based on an equivalent system mod...
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In this paper, an iterative soft multiuser detection (MUD) algorithm is proposed for multiple-input multiple-output multi-carrier code-division multiple access (MIMO MC-CDMA) systems. Based on an equivalent system model, an efficient soft MUD algorithm is first derived by the central limit theorem, the property of the complex Gaussian distribution, and fast matrix computation formulas. By iteratively using the soft MUD algorithm with some updated probability information, we then obtain the proposed iterative soft MUD algorithm. Finally, it is shown that this algorithm achieves near-optimal performance with very efficient iterative computations.
This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering th...
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This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments.
In this paper, we use the Yamada's method to modify the normal Mann's iterative process to have strong convergence for a k-strictly pseudo-contractive mapping in the framework of Hilbert spaces.
In this paper, we use the Yamada's method to modify the normal Mann's iterative process to have strong convergence for a k-strictly pseudo-contractive mapping in the framework of Hilbert spaces.
In this paper we examine the use of low-density parity-check (LDPC) codes in binary asymmetric channels. The problem is interesting since in some types of binary input fading multiple access channels (MAC) without cha...
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In this paper we examine the use of low-density parity-check (LDPC) codes in binary asymmetric channels. The problem is interesting since in some types of binary input fading multiple access channels (MAC) without channel state information (CSI), which use the successive decoding scheme, some of the users may experience asymmetric channels. It is well known that the successive decoder is a set of single user decoders and since there is no CSI at the receiver, the corresponding single user channels may be asymmetric in general. In that case the rate of interest of the user with the asymmetric channel is achieved by an unbalanced input distribution of the binary input. We are interested in constructing LDPC codes for these channels that approach the desired rate tuple in the capacity region. A convenient way of making the output distribution unbalanced is by introducing a mapper at the output of the encoder. Here we explain the method of mapping and its effect on the iterative decoding and derive closed form expressions for the upper bound of the probability of error.
This paper proposes an algorithm that solves planar homography by iterative linear optimization. We iteratively employ direct linear transformation (DLT) algorithm to robustly estimate the homography induced by a give...
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This paper proposes an algorithm that solves planar homography by iterative linear optimization. We iteratively employ direct linear transformation (DLT) algorithm to robustly estimate the homography induced by a given set of point correspondences under perspective transformation. By simple on-the-fly homogeneous coordinate adjustment we progressively minimize the difference between the algebraic error and the geometric error. When the difference is sufficiently close to zero, the geometric error is equivalently minimized and the homography is reliably solved. Backward covariance propagation is employed to do error analysis. The experiments prove that the algorithm is able to find global minimum despite erroneous initialization. It gives very precise estimate at low computational cost and greatly outperforms existing techniques.
This paper explores two types of multistate Hopfield neural networks, based on commutative quaternions that are similar to Hamilton's quaternions but with commutative multiplication. In one type of the networks, t...
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This paper explores two types of multistate Hopfield neural networks, based on commutative quaternions that are similar to Hamilton's quaternions but with commutative multiplication. In one type of the networks, the state of a neuron is represented by two kinds of phases and one real number. The other type of the networks adopts the decomposed form of commutative quaternion, i.e., the state of a neuron consists of a combination of two complex values. We have investigated the stabilities of these networks, i.e., the energies monotonically decreases with respect to the changes of the network states.
Let H be a real Hilbert *** that T is a nonexpansive mapping on H with a fixed point, G is a L-Lipschitzian mapping on H with coefficient L > 0, and F : H → H is a k- Lipschitzian and η-strongly monotone operator...
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Let H be a real Hilbert *** that T is a nonexpansive mapping on H with a fixed point, G is a L-Lipschitzian mapping on H with coefficient L > 0, and F : H → H is a k- Lipschitzian and η-strongly monotone operator with k > 0, η > O. Let 0 2, 0 2/2)/L = τ/L. We pointed out the relationship between Yamada's method and viscosity iteration and proved that the sequence {x η } generated by the iterative method x η+1 = α n γG(x n ) + (I - μα n F)Tx n converges strongly to a fixed point x̃ ∈ F ix (T), which solves the variational inequality ((γG - μF)x̃, x-x̃) ≤ 0, for x ∈ F ix (T).
Vision plays the most important role in human perception, which is limited to only the visual band of the electromagnetic spectrum. Therefore, the need for Radar imaging systems, to recover some sources that are not w...
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Vision plays the most important role in human perception, which is limited to only the visual band of the electromagnetic spectrum. Therefore, the need for Radar imaging systems, to recover some sources that are not within human visual band, is raised. This paper presents a new algorithm for Synthetic Aperture Radar (SAR) images segmentation based on thresholding technique. Generally, segmentation of a SAR image falls into two categories;one based on grey levels and the other based on texture. The present paper deals with SAR images segmentation based on grey levels. We developed a new formula using Minimum Cross Entropy Thresholding (MCET) method for estimating optimal threshold value based on Gamma distribution to analyzing data on images;that means histogram of SAR images is assumed to be a mixture of Gamma distributions. The proposed method is iterative which decreases the number of operation to converge tends to the optimal solution. It is applied on bi-modal and multimodal scenarios. The results obtained are promising.
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