Sentence examples for more recent neural from inspiring English sources

Commonly applied methods include principal component analysis (PCA), various forms of cluster analysis (CA), and discriminant analysis (DA, both linear and quadratic), followed by more recent (neural network and fuzzy) methods [17], although the application of combined techniques has been reported in the literature [28].

More recent neural network models such as back-propagation [8], [9] and basis function networks [10], [11] are simply non-linear extensions of the originally proposed models in the sense that they implement a mapping from stimulus to motor response by adapting (synaptic) weights in networks with fixed topology.

A more recent neural mass model, the Jansen-Rit model [ 62], is obtained when the impulse response function has the form g(t) = Gkte− kt.

This is to some extent consistent with analysis-by-synthesis proposed in motor theories of speech perception (Studdert-Kennedy et al. 1970; Liberman and Whalen 2000), and in more recent neural accounts (cf. Davis and Johnsrude 2007; Poeppel and Monahan 2011).

Using hydrological data (daily discharge, rainfall, and mean, maximum and minimum air temperatures) from the Upper Narew River watershed in Poland, the forecasting performance of DLBM was compared to that of traditional multiple linear regression (MLR) and more recent artificial neural network (ANN) based models.

This work is concerned with the first of these aspects: it proposes novel strategies for ESN reservoir design based on the theoretical framework built by Kohonen׳s classical works on self-organization – which includes the notions of short-range positive feedback and lateral inhibition – and also on the related and more recent notion of neural gas.

While the focus of earlier studies lies mainly on volumetric differences using VBM, more recent studies investigated neural fiber tracts using diffusion tensor imaging (DTI) to analyze the white matter microstructure.

Early studies focused mainly on gray and white matter differences using voxel-based morphometry, while more recent studies investigated neural fiber tracts using diffusion tensor imaging (DTI) to analyze the white matter microstructure.

Previously, several ancient SINES have been implicated in neural functions (Santangelo et al. 2007; Franchini et al. 2011; Tashiro et al. 2011), and our data, along with other studies (Britten 2010), suggest that there may be more recent SINE-driven neural adaptations.

More recent studies on how neural input regulates cerebrovascular tone and blood flow have resulted in the rediscovery of the 'neurovascular unit'.

More recent and sophisticated methods like Neural Networks or Support Vector Machine methods are required to fully exploit the potential of the complementary information provided by our approach.