A nonlinear redundant lifting wavelet packet algorithm was put forward in this study. For the node signals to be decomposed in different layers, predicting operators and updating operators with different orders of vanishing moments were chosen to take norm l(p) of the scale coefficient and wavelet coefficient acquired from decomposition, the predicting operator and updating operator correspondi...

We introduce a coe cient update procedure into existing batch and online dictionary learning algorithms. We rst propose an algorithm which is a coe cient updated version of the Method of Optimal Directions (MOD) dictionary learning algorithm (DLA). The MOD algorithm with coe cient updates presents a computationally expensive dictionary learning iteration with high convergence rate. Secondly, we...

Diffusion-limited aggregation (DLA) is a useful model for studying such common physical phenomena as dust clustering, unstable fluid flowJ chemical species precipitation, and crystal growth. Simulating the DLA processes using electrostatic analogy is very computation-intensive. Elimination of closed loops in DLA images can significantly reduce the dimensionality of the problem and minimize the ...

A parallel algorithm for diffusion-limited aggregation (DLA) is described and analyzed from the perspective of computational complexity. The dynamic exponent z of the algorithm is defined with respect to the PRAM model of parallel computation according to T ∼ L z , where T is the running time and L the cluster size. It is argued that z = D − D 2 /3, where D is the fractal dimension and D 2 is t...

Diffusion-Limited Aggregation (DLA) is a model of fractal growth. Computer models can simulate the fast aggregation of millions of particles. In this paper, we propose a modified version of DLA, called semantically modified DLA (SM-DLA), for visualizing large-scale networks. SM-DLA introduces similarity measures between particles so that instead of attaching to the nearest particle in the aggre...

In this paper, a new algorithm is developed to reduce the computational complexity of Ward’s method. The proposed approach uses a dynamic k-nearest-neighbor list to avoid the determination of a cluster’s nearest neighbor at some steps of the cluster merge. Double linked algorithm (DLA) can significantly reduce the computing time of the fast pairwise nearest neighbor (FPNN) algorithm by obtainin...

This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized au...

This paper describes a new multilevel decomposition method for the separation of convolutive image mixtures. The proposed method uses an Adaptive Quincunx Lifting Scheme (AQLS) based on wavelet decomposition to preprocess the input data, followed by a Non-Negative Matrix Factorization whose role is to unmix the decomposed images. The unmixed images are, thereafter, reconstructed using the inver...

We address some key issues in designing dense linear algebra (DLA) algorithms that are common for both multi/many-cores and special purpose architectures (in particular GPUs). We present them in the context of an LU factorization algorithm, where randomization techniques are used as an alternative to pivoting. This approach yields an algorithm based entirely on a collection of small Level 3 BLA...

We suggest the parallel computational complexity of simulating a system as a measure of its physical complexity. As an example, we present a parallel algorithm for simulating diiusion-limited aggregation (DLA) and calculate the algorithm's dynamic exponent z, which gives the scaling of the average running time with cluster radius. It is plausible that the algorithm attains the minimum possible ...