This work addresses the problem of covariance matrix estimation for ocean clutter modeling. For ship detection based on polarimetric synthetic aperture radar (PolSAR) imagery and constant false alarm rate (CFAR) detectors, accurate ocean clutter modeling is essential. The covariance matrix provides all the polarimetric information of the ocean clutter and its estimate is always involved in PolS...

We present a fast addition algorithm in the Jacobian of a genus 3 non-hyperelliptic curve over a field of any characteristic. When the curve has a rational flex and char(k) > 5, the computational cost for addition is 148M + 15SQ + 2I and 165M + 20SQ + 2I for doubling. An appendix focuses on the computation of flexes in all characteristics. For large odd q, we also show that the set of rational ...

We describe a graph coloring problem associated with the determination of mathematical derivatives. The coloring instances are obtained as intersection graphs of row partitioned sparse derivative matrices. The size of the graph is dependent on the partition and can be varied between the number of columns and the number of nonzero entries. If solved exactly our proposal will yield a significant ...

We present completely new very powerful solutions to two fundamental problems central to computer vision. 1. Given data sets representing C objects to be stored in a database, and given a new data set for an object, determine the object in the database that is most like the object measured. We solve this problem through use of PIMs ("Polynomial Interpolated Mea-sures"), which is a new represent...

High rates of corporate taxation reduce corporate investment and thereby depress local wages. Using cross-country data I estimate that a ten percentage point increase in the corporate tax rate of high-income countries reduces mean annual gross wages by seven percent. The results do not support the common belief that the burden of corporate taxes falls most heavily on skilled labor; corporate ta...

In this paper we derive an algorithm that computes the entire solution path of the support vector regression, with essentially the same computational cost as fitting one SVR model. We also propose an unbiased estimate for the degrees of freedom of the SVR model, which allows convenient selection of the regularization parameter.

We propose a multiobjective strategy for model predictive control (MPC) that we term utopiatracking MPC. The controller minimizes, in some norm, the distance of its cost vector to that of the unreachable steady-state utopia point. Stability is ensured by using a terminal constraint to a selected point along the steady-state Pareto front. One of the key advantages of this approach is that multip...

Abstract We have proposed a block sparse approximate inverse with cutoff (BSAIC) preconditioner for relatively dense matrices. The BSAIC preconditioner is effective for semi-sparse matrices which have relatively large number of nonzero elements. This method reduces the computational cost for generating the preconditioning matrix, and overcomes the performance bottlenecks of SAI using the blocke...

Organic solar cells (OSCs) with a bulk-heterojunction (BHJ) are promising energy conversion devices, because they are flexible and environmental-friendly, and can be fabricated by low-cost roll-to-roll process. Here, we systematically investigated the interrelations between photovoltaic properties and the domain morphology of the active layer in OSCs based on films of poly-(9,9-dioctylfluorene-...

Operations on Sparse Matrices are the key computational kernels in many scientific and engineering applications. They are characterized with poor substantiated performance. It is not uncommon for microprocessors to gain only 10-20% of their peak floating-point performance when doing sparse matrix computations even when special vector processors have been added as coprocessor facilities. In this...