Search results for "present"
showing 10 items of 3598 documents
Wronskian Addition Formula and Darboux-Pöschl-Teller Potentials
2013
For the famous Darboux-Pöschl-Teller equation, we present new wronskian representation both for the potential and the related eigenfunctions. The simplest application of this new formula is the explicit description of dynamics of the DPT potentials and the action of the KdV hierarchy. The key point of the proof is some evaluation formulas for special wronskian determinant.
SAN plot: A graphical representation of the signal, noise, and artifacts content of spectra
2019
The signal-to-noise ratio is an important property of NMR spectra. It allows to compare the sensitivity of experiments, the performance of hardware, etc. Its measurement is usually done in a rudimentary manner involving manual operation of selecting separately a region of the spectrum with signal and noise, respectively, applying some operation and returning the signal-to-noise ratio. We introduce here a simple method based on the analysis of the distribution of point intensities in one- and two-dimensional spectra. The signal/artifact/noise plots, (SAN plots) allows one to present in a graphical manner qualitative and quantitative information about spectra. It will be shown that besides me…
Artificial intelligence techniques for cancer treatment planning
1988
An artificial intelligence system, NEWCHEM, for the development of new oncology therapies is described. This system takes into account the most recent advances in molecular and cellular biology and in cell-drug interaction, and aims to guide experimentation in the design of new optimal protocols. Further work is being carried out, aimed to embody in the system all the basic knowledge of biology, physiopathology and pharmacology, to reason qualitatively from first principles so as to be able to suggest cancer therapies.
An associative link from geometric to symbolic representations in artificial vision
1991
Recent approaches to modelling the reference of internal symbolic representations of intelligent systems suggest to consider a computational level of a subsymbolic kind. In this paper the integration between symbolic and subsymbolic processing is approached in the framework of the research work currently carried on by the authors in the field of artificial vision. An associative mapping mechanism is defined in order to relate the constructs of the symbolic representation to a geometric model of the observed scene.
A New Unsupervised Neural Network for Pattern Recognition with Spiking Neurons
2006
In this paper we propose a three-layered neural network for binary pattern recognition and memorization. Unlike the classic approach to pattern recognition, our net works organizing itself in an unsupervised way, to distinguish beetween different patterns or to recognize similar ones. If we present a binary input to the first layer, after some time steps we could read the output of the net in the third layer, as one and only one neuron activating with high firing rate; the middle layer will act as a generalization layer, i.e. similar pattern will have similar (or the same) representation in the middle layer. We used learning algorithms inspired from other works or from biological data to ac…
Hybrid architecture for shape reconstruction and object recognition
1998
The proposed architecture is aimed to recover 3-D- shape information from gray-level images of a scene; to build a geometric representation of the scene in terms of geometric primitives; and to reason about the scene. The novelty of the architecture is in fact the integration of different approaches: symbolic reasoning techniques typical of knowledge representation in artificial intelligence, algorithmic capabilities typical of artificial vision schemes, and analogue techniques typical of artificial neural networks. Experimental results obtained by means of an implemented version of the proposed architecture acting on real scene images are reported to illustrate the system capabilities.
A spiking network for body size learning inspired by the fruit fly
2013
The concept of peripersonal space is an interesting research topics for psychologists, neurobiologists and for robotic applications. A living being can learn the representation of its own body to take the correct behavioral decision when interacting with the world. To transfer these important learning mechanisms on bio-robots, simple and efficient solutions can be found in the insect world. In this paper a neural-based model for body-size learning is proposed taking into account the results obtained in experiments with fruit flies. Simulations and experimental results on a roving platform are reported and compared with the biological counterpart.
Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators
2021
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…
Internal Simulation of an Agent’s Intentions
2013
We present the Associative Self-Organizing Map (A-SOM) and propose that it could be used to predict an agent’s intentions by internally simulating the behaviour likely to follow initial movements. The A-SOM is a neural network that develops a representation of its input space without supervision, while simultaneously learning to associate its activity with an arbitrary number of additional (possibly delayed) inputs. We argue that the A-SOM would be suitable for the prediction of the likely continuation of the perceived behaviour of an agent by learning to associate activity patterns over time, and thus a way to read its intentions.
The Cercle de l’Ermitage by Alberto Sartoris. Axonometry as a Synthetic Representation of the Project
2022
Analisi della cromolitografia di Alberto Sartoris pubblicata nel 1936 dalla rivista The Architectural Review. Analysis of Alberto Sartoris' chromolithography published in 1936 in The Architectural Review.