This paper presents a reduced-complexity, fixed-point algorithm and efficient real-time VLSI architectures for multiuser channel estimation, one of the core baseband processing operations in wireless base-station receivers for CDMA. Future wireless base-station receivers will need to use sophisticated algorithms to support extremely high data rates and multimedia. Current DSP implementations of...

SUMMARY Existing multigrid techniques are used to eeect an eecient method for reconstructing an image from noisy, blurred data. Total Variation minimization yields a nonlinear integro-diierential equation which, when discretized using cell-centered-nite diierences, yields a full matrix equation. A xed point iteration is applied with the intermediate matrix equations solved via a preconditioned ...

In this paper we propose a numerical method to obtain an approximation of Nash equilibria for multi-player non-cooperative games with a special structure. We consider the infinite horizon problem in a case which leads to a system of Hamilton-Jacobi equations. The numerical method is based on the Dynamic Programming Principle for every equation and on a global fixed point iteration. We present t...

Let $C$ be a nonempty closed convex subset of a real Hilbert space $H$. Let ${S_n}$ and ${T_n}$ be sequences of nonexpansive self-mappings of $C$, where one of them is a strongly nonexpansive sequence. K. Aoyama and Y. Kimura introduced the iteration process $x_{n+1}=beta_nx_n+(1-beta_n)S_n(alpha_nu+(1-alpha_n)T_nx_n)$ for finding the common fixed point of ${S_n}$ and ${T_n}$, where $uin C$ is ...

DEA methodology allows DMUs to select the weights freely, so in the optimalsolution we may see many zeros in the optimal weight. to overcome this prob-lem, there are some methods, but they are not suitable for evaluating DMUswith fuzzy data. In this paper, we propose a new method for solving fuzzyDEA models with restricted multipliers with less computation, and comparethis method with Liu''''''...

We develop and compare multilevel algorithms for solving constrained nonlinear variational problems via interior point methods. Several equivalent formulations of the linear systems arising at each iteration of the interior point method are compared from the point of view of conditioning and iterative solution. Furthermore, we show how a multilevel continuation strategy can be used to obtain go...

In this paper we propose a structure-preserving doubling algorithm (SDA) for computing the minimal nonnegative solutions to the nonsymmetric algebraic Riccati equation (NARE) based on the techniques developed in the symmetric cases. This method allows the simultaneous approximation of the minimal nonnegative solutions of the NARE and its dual equation, only requires the solutions of two linear ...

Let X, d be a complete metric space and T a self-map of X. Let xn 1 f T, xn be some iteration procedure. Suppose that F T , the fixed point set of T , is nonempty and that xn converges to a point q ∈ F T . Let {yn} ⊂ X and define n d yn 1, f T, yn . If lim n 0 implies that limyn q, then the iteration procedure xn 1 f T, xn is said to be T -stable. Without loss of generality, we may assume that ...

Making use of last derivative approximation and weight function approach, we construct an eighth-order class of three-step methods, which are consistent with the optimality conjecture of Kung-Traub for constructing multi-point methods without memory. Per iteration, any method of the developed class is totally free from derivative evaluation. Such classes of schemes are more practical when the c...

The deterministic convergence for a Double Parallel Feedforward Neural Network (DPFNN) is studied. DPFNN is a parallel connection of a multi-layer feedforward neural network and a single layer feedforward neural network. Gradient method is used for training DPFNN with finite training sample set. The monotonicity of the error function in the training iteration is proved. Then, some weak and stro...