Image classification was performed using Gabor wavelet filters for image feature extraction, self-organising maps (SOM) for dimensional reduction of Gabor wavelet filters, and forward (FNN), Hermite (HNN) and Laguerre (LNN) neural networks to classify real and artificial fingerprint images from optical coherence tomography (OCT). Use of a SOM after Gabor edge detection of OCT images of fingerpr...

While the standard approach to quantum systems studies length preserving linear transformations of wave functions, the Markov picture focuses on trace preserving operators on the space of Hermitian (self-adjoint) matrices. The Markov approach extends the standard one and provides a refined analysis of measurements and quantum Markov chains. In particular, Bell’s inequality becomes structurally ...

With the help of the Penrose-Ward transform, which relates certain holomorphic vector bundles over the supertwistor space to the equations of motion of self-dual SYM theory in four dimensions, we construct hidden infinite-dimensional symmetries of the theory. We also present a new and shorter proof (cf. hep-th/0412163) of the relation between certain deformation algebras and hidden symmetry alg...

We present a detailed analytical study of a paradigmatic scale-free network model, the Static Model. Analytical expressions for its main properties are derived by using the hidden variables formalism. We map the model into a canonic hidden variables one, and solve the latter. The good agreement between our predictions and extensive simulations of the original model suggests that the mapping is ...

We study the possibility that a keV-MeV mass hidden photon (HP), i.e. a hidden sector U(1) gauge boson, accounts for the observed amount of dark matter. We focus on the case where the HP interacts with the standard model sector only through kinetic mixing with the photon. The relic abundance is computed including all relevant plasma effects into the photon’s self-energy, which leads to a resona...

In this paper we present upper bounds for the learning rates for hybrid models that employ a combination of both self-organized and supervised learning, using radial basis functions to build receptive field representations in the hidden units. The learning performance in such networks with nearest neighbor heuristic can be improved upon by multiplying the individual receptive field widths by a ...

The following piece, “Escondido”, came as a reflection after partaking in the 2022 Lavender Languages Institute reading article titled: Complexity of “x” Latinx: How Latinx/a/o Students Relate to, Identify with, and Understand Term Latinx (Salinas, 2020). I self-identify throughout week at Institute, reflected on what meant to me. My initial understanding was that term would allow me express my...

To improve recognition and generalization capability of back-propagation neural networks (BPNN), a hidden layer self-organization inspired by immune algorithm called SONIA, is proposed. B cell construction mechanism of immune algorithm inspires a creation of hidden units having local data recognition ability that improves recognition capability. B cell mutation mechanism inspires a creation of ...

In this paper, a three-layer force-directed self-organizing map is designed to resolve the circuit placement problem with arbitrarily shaped rectilinear modules. The proposed neural model with an additional hidden layer can easily model a rectilinear module by a set of hidden neurons to correspond the partitioned rectangles. With the collective computing from hidden neurons, these rectilinear m...

Mobile Ad Hoc network is a self-organizing infrastructure less network where the nodes are responsible for routing the packets. MANET has dynamic topology which allows nodes to join and leave the network at any time. This paper proposes a channel adaptive routing protocol which extends AOMDV routing protocol to accommodate channel fading. The proposed Channel Aware AOMDV protocol uses channel a...