Design of finite-word-length FIR filters with least-squares error

Other advantages of our ProjPSO algorithm over current methods are (1) our experience is that the time required to generate the optimal design is gen- erally a lot faster than many

Real Schur and Hessenberg-triangular forms The doubly shifted QZ algorithm.. Above algorithm is locally

Then, we recast the signal recovery problem as a smoothing penalized least squares optimization problem, and apply the nonlinear conjugate gradient method to solve the smoothing

Then, we recast the signal recovery problem as a smoothing penalized least squares optimization problem, and apply the nonlinear conjugate gradient method to solve the smoothing

Then, it is easy to see that there are 9 problems for which the iterative numbers of the algorithm using ψ α,θ,p in the case of θ = 1 and p = 3 are less than the one of the

In this chapter we develop the Lanczos method, a technique that is applicable to large sparse, symmetric eigenproblems.. The method involves tridiagonalizing the given

These possibilities are associated with totally di↵erent underlying dynam- ics for electroweak symmetry breaking than the SM, requiring new physics beyond the Higgs around the

we often use least squares to get model parameters in a fitting problem... 7 Least