Consistent description of nuclear charge radii and electric monopole transitions

A systematic study of energy spectra throughout the rare-earth region (even-even nuclei from $_{58}$Ce to $_{74}$W) is carried out in the framework of the interacting boson model (IBM), leading to an accurate description of the spherical-to-deformed shape transition in the different isotopic chains. The resulting IBM Hamiltonians are then used for the calculation of nuclear charge radii (including isotope and isomer shifts) and electric monopole transitions with consistent operators for the two observables. The main conclusion of this study is that an IBM description of charge radii and electric monopole transitions is possible for most of the nuclei considered but that it breaks down in the tungsten isotopes. It is suggested that this failure is related to hexadecapole deformation.Comment: 13 pages, 5 tables, 3 figures, accepted for publication in Physical Review

Higher-rank discrete symmetries in the IBM. I Octahedral shapes: general Hamiltonian

In the context of the interacting boson model with $s$, $d$ and $g$ bosons, the conditions for obtaining an intrinsic shape with octahedral symmetry are derived for a general Hamiltonian with up to two-body interactions.Comment: 19 pages, 2 figures, accepted for publication in Nuclear Physics

Analysis of the sign regressor least mean fourth adaptive algorithm

A novel algorithm, called the signed regressor least mean fourth (SRLMF) adaptive algorithm, that reduces the computational cost and complexity while maintaining good performance is presented. Expressions are derived for the steady-state excess-mean-square error (EMSE) of the SRLMF algorithm in a stationary environment. A sufficient condition for the convergence in the mean of the SRLMF algorithm is derived. Also, expressions are obtained for the tracking EMSE of the SRLMF algorithm in a nonstationary environment, and consequently an optimum value of the step-size is obtained. Moreover, the weighted variance relation has been extended in order to derive expressions for the mean-square error (MSE) and the mean-square deviation (MSD) of the proposed algorithm during the transient phase. Computer simulations are carried out to corroborate the theoretical findings. It is shown that there is a good match between the theoretical and simulated results. It is also shown that the SRLMF algorithm has no performance degradation when compared with the least mean fourth (LMF) algorithm. The results in this study emphasize the usefulness of this algorithm in applications requiring reduced implementation costs for which the LMF algorithm is too complex

Properties of isocalar-pair condensates

It is pointed out that the ground state of n neutrons and n protons in a single-j shell, interacting through an isoscalar (T=0) pairing force, is not paired, J=0, but rather spin-aligned, J=n. This observation is explained in the context of a model of isoscalar P (J=1) pairs, which is mapped onto a system of p bosons, leading to an approximate analytic solution of the isoscalar-pairing limit in jj coupling.Comment: 7 pages, 3 figures, 1 tabl

Performance of the multilayer perceptron-based DFE with latticestructure in linear and non-linear channels

The effect of whitening the input data in a multilayer perceptron (MLP)-based decision feedback equalizer (DFE) is evaluated. It is shown that whitening the received data employing adaptive lattice channel equalization algorithms improves the convergence rate and bit error rate performances of MLP-based decision feedback equalizers. The consistency in performance is observed in time-invariant, time-varying and non-linear channel

Performance of the multilayer perceptron-based DFE with latticestructure in linear and non-linear channels

The effect of whitening the input data in a multilayer perceptron (MLP)-based decision feedback equalizer (DFE) is evaluated. It is shown that whitening the received data employing adaptive lattice channel equalization algorithms improves the convergence rate and bit error rate performances of MLP-based decision feedback equalizers. The consistency in performance is observed in time-invariant, time-varying and non-linear channel

Tracking analysis of normalized adaptive algorithms

Tracking analysis of normalized adaptive algorithms is carried out in the presence of two sources of nonstationarities: carrier frequency offset between transmitter and receiver; random variations in the environment. A unified approach is carried out using a mixed-norm-type error nonlinearity. Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset

Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm

In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. Sufficient and necessary conditions for the convergence of the algorithm are derived. Furthermore, bounds on the step size to ensure convergence of the LMF algorithm are also derive

An improved HIC using a new ordering and grouping algorithm

A linear group-wise successive interference canceller in a synchronous CDMA system is considered in this work. The proposed hybrid detector that combines successive and parallel cancellation techniques makes use of advantages offered by the two techniques. The convergence of the hybrid interference cancellation (HIC) detector is guaranteed by an adjustable parameter that depends upon the largest eigenvalue of the system's transition matrix. Since this largest eigenvalue is difficult to estimate, an upper bound is necessary for successful convergence. For this reason, we propose a new ordering and grouping algorithm that yields a tight upper bound, which, in turn, results in a higher convergence speed. Simulation results show that a significant improvement in performance is obtained when this technique is used