If a polynomial is expanded in terms of Bernstein polynomial over an interval then the coefficients of the expansion may be used to provide upper and lower bounds for the value of the polynomial over the interval. Whe...
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If a polynomial is expanded in terms of Bernstein polynomial over an interval then the coefficients of the expansion may be used to provide upper and lower bounds for the value of the polynomial over the interval. When applying this method to interval polynomials straightforwardly, the coefficients of the expansion are computed with an increase in width due to dependency intervals. In this paper we show that if the computations are rearranged suitably then the Bernstein coefficients can be computed with no increase in width due to dependency intervals.
Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be emp...
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Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/interharmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.
Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energyefficient viewpoint, we de...
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Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energyefficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843? 1864 (1960)] and [J. Sawada, D. S. Modha, ?Synapse: Scalable energy-efficient neurosynaptic computing? in Application of Concurrency to System Design (ACSD) (2013), pp. 14?15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a 108-fold discrepancy between biological and lowest possible values of a neuron?s computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).
A sensible assumption in psycholinguistics is that universal principles of optimal computation guide structural decisions made during sentence processing. This idea was questioned by the apparent cross-linguistic vari...
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A sensible assumption in psycholinguistics is that universal principles of optimal computation guide structural decisions made during sentence processing. This idea was questioned by the apparent cross-linguistic variation in Relative Clause attachment: a wealth of experimental results from the nineties showed that speakers of Spanish, among other languages, more readily converged towards the least optimal structural resolution (i.e. non-local attachment) challenging the universality of parsing principles of locality. A more recent development in this literature demonstrated that previous results were confounded by the availability of an additional parse, the socalled Pseudo-Relative, in the ill-behaved languages (Grillo 2012;Grillo & Costa 2014). Grillo and colleagues further suggested that the parser more readily disambiguates in favour of the Pseudo-Relative reading, when possible, because of its structural and interpretive simplicity in comparison to Relative Clauses and that non-local attachment is a direct consequence of this independent preference. We present novel results in support of this account from two offline forced-choice attachment questionnaires in Spanish. The results show that Pseudo-Relative availability significantly affects attachment preferences and that cross-linguistic variation in Relative Clause attachment is likely to be epiphenomenal and largely attributable to underlying grammatical differences.
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