How is Block’s Central Argument against Functionalism?

Block argued against functionalism. The argument was metaphorized by building a normal body but with the brain of a homunculus. A review of the metaphorization exposes that the argument is inadequate to avoid the weakness of the functionalist doctrine

Conversion of neutron stars to strange stars as a possible origin of γ-ray bursts

We propose that some neutron stars in low-mass x-ray binaries can accrete sufficient mass to undergo a phase transition to become strange stars. The energy released per conversion event satisfies the requirements of cosmological y-ray bursts, and the Lorentz factor of the resultant expanding fireball may exceed 5 × 103 because the strange star has very low baryon contamination. The model burst rate is consistent with observations.published_or_final_versio

Local polynomial modeling and bandwidth selection for time-varying linear models

This paper proposes a local polynomial modeling approach and bandwidth selection algorithm for estimating time-varying linear models (TVLM). The time-varying coefficients of a TVLM are modeled locally by polynomials and estimated using least-squares estimation with a kernel having a certain bandwidth or support. Asymptotic behavior of the proposed estimator is established and it shows that there exists an optimal local bandwidth which minimizes the weighted mean squared error (MSE). A data-driven variable bandwidth selection method is also proposed to estimate this optimal bandwidth. Simulation results show that the proposed LPM method with adaptive bandwidth selection outperforms conventional TVLM identification methods in a large variety of testing conditions. ©2009 IEEE.published_or_final_versionThe 7th International Conference on Information, Communications and Signal Processing (ICICS 2009), Macau, China, 8-10 December 2009. In Proceedings of the International Conference on Information, Communications and Signal Processing, 2009, p. 1-

Local polynomial modeling and variable bandwidth selection for time-varying linear systems

This paper proposes a local polynomial modeling (LPM) approach and variable bandwidth selection (VBS) algorithm for identifying time-varying linear systems (TVLSs). The proposed method models the time-varying coefficients of a TVLS locally by polynomials, which can be estimated by least squares estimation with a kernel having a certain bandwidth. The asymptotic behavior of the proposed LPM estimator is studied, and the existence of an optimal local bandwidth which minimizes the local mean-square error is established. A new data-driven VBS algorithm is then proposed to estimate this optimal variable bandwidth adaptively and locally. An individual bandwidth is assigned for each coefficient instead of the whole coefficient vector so as to improve the accuracy in fast-varying systems encountered in fault detection and other applications. Important practical issues such as online implementation are also discussed. Simulation results show that the LPM-VBS method outperforms conventional TVLS identification methods, such as the recursive least squares algorithm and generalized random walk Kalman filter/smoother, in a wide variety of testing conditions, in particular, at moderate to high signal-to-noise ratio. Using local linearization, the LPM method is further extended to identify time-varying systems with mild nonlinearities. Simulation results show that the proposed LPM-VBS method can achieve a satisfactory performance for mildly nonlinear systems based on appropriate linearization. Finally, the proposed method is applied to a practical problem of voltage-flicker-tracking problem in power systems. The usefulness of the proposed approach is demonstrated by its improved performance over other conventional methods. © 2006 IEEE.published_or_final_versio

Harmonic analysis of power system signals using a new regularized adaptive windowed lomb periodogram

This paper proposes a new regularized adaptive windowed Lomb periodogram (RAWLP) method for time-frequency analysis of non-stationary power signals. It extends the conventional Lomb periodogram by estimating the periodogram locally using the weighted least-squares (WLS) estimator. Instead of employing one constant window in WLS, variable window bandwidth is adaptively selected by the intersection of confidence intervals (ICI) method to achieve a better tradeoff between time resolution and frequency resolution. Furthermore, regularization techniques are incorporated in the AWLP to further improve its performance by reducing the variance of the estimator. Simulation results show that the proposed RAWLP method has superior performance over windowed Lomb periodogram with one constant bandwidth for estimating the harmonic and interharmonic frequencies in power systems. © 2010 IEEE.published_or_final_versionThe 1st International Conference on Green Circuits and Systems (ICGCS 2010), Shanghai, China, 21-23 June 2010. In Proceedings of the 1st ICGCS, 2010, p. 567-57

Are soft γ-ray repeaters strange stars?

The soft γ-ray repeaters (SGRs) are proposed to result from young, magnetized strange stars with superconducting cores. As such a strange star spins down, the quantized vortex lines move outward and drag the magnetic flux tubes because of the strong coupling between them. Since the terminations of the tubes interact with the stellar crust, the dragged tubes can produce sufficient tension to crack the crust and pull parts of the broken platelet into the quark core. The deconfinement of crustal matter into strange quark matter will release energy. The model burst energy, duration, time interval, spectrum, and the persistent x-ray emission from SGRs are shown to be in agreement with observed results.published_or_final_versio

A new Kalman filter-based algorithm for adaptive coherence analysis of non-stationary multichannel time series

IEEE International Symposium on Circuits and Systems, Island of Kos, Greece, 21-24 May 2006This paper proposes a new Kalman filter-based algorithm for multichannel autoregressive (AR) spectrum estimation and adaptive coherence analysis with variable number of measurements. A stochastically perturbed k -order difference equation constraint model is used to describe the dynamics of the AR coefficients and the intersection of confidence intervals (ICI) rule is employed to determine the number of measurements adaptively to improve the timefrequency resolution of the AR spectrum and coherence function. Simulation results show that the proposed algorithm achieves a better time-frequency resolution than conventional algorithms for non-stationary signals. © 2006 IEEE.published_or_final_versio