111,461 research outputs found
Modal Considerations on Information Processing and Computation in the Nervous System
We can characterize computationalism very generally as a complex thesis with two main parts: the thesis that the brain (or the nervous system) is a computational system and the thesis that neural computation explains cognition. As Piccinini and Bahar (2012) point out, over the last six decades, computationalism has been the mainstream theory of cognition. Nevertheless, there is still substantial debate about which type of computation explains cognition, and computationalism itself still remains controversial. My aim in this paper is to make two main contributions to the debate about the first subthesis of computationalism, i.e. that the brain is a computational system. First, I want to offer an accurate elucidation of the notion relevant for understanding computationalism (the notion of computation) and clarify the relation between computation and information as well as the relations between both computation and information processing and the nervous system. Second, I want to argue against a peculiar form of computationalism: the thesis that neural processes are constitutively computational in some sense; that neural processes cannot be realized by a system that is not in some sense computational. I will call this thesis "modal computationalism". In particular, I want to argue that neural processing can be realized by a system that is not a sui generis computer (i. e., a computing system that is neither digital nor analog) and by a system that is not a generic computer (a computer in the most general sense: one that includes digital, analog, and any other kind of computation). Actual neural processing is presumed to be computational in these two senses (Piccinini and Bahar 2012). I will argue that, even if this is true, neural processing can be realized by a computing system that is not of the same kind as those that perform actual neural processing and even by a system that is not computational at all.Fil: Wajnerman Paz, Abel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin
Indirect test of M-S circuits using multiple specification band guarding
Testing analog and mixed-signal circuits is a costly task due to the required test time targets and high end technical resources. Indirect testing methods partially address these issues providing an efficient solution using easy to measure CUT information that correlates with circuit performances. In this work, a multiple specification band guarding technique is proposed as a method to achieve a test target of misclassified circuits. The acceptance/rejection test regions are encoded using octrees in the measurement space, where the band guarding factors precisely tune the test decision boundary according to the required test yield targets. The generated octree data structure serves to cluster the forthcoming circuits in the production testing phase by solely relying on indirect measurements. The combined use of octree based encoding and multiple specification band guarding makes the testing procedure fast, efficient and highly tunable. The proposed band guarding methodology has been applied to test a band-pass Butterworth filter under parametric variations. Promising simulation results are reported showing remarkable improvements when the multiple specification band guarding criterion is used.Peer ReviewedPostprint (author's final draft
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Systems and methods for physiological signal enhancement and biometric extraction using non-invasive optical sensors
A system and method for signal processing to remove unwanted noise components including: (i) wavelength-independent motion artifacts such as tissue, bone and skin effects, and (ii) wavelength-dependent motion artifact/noise components such as venous blood pulsation and movement due to various sources including muscle pump, respiratory pump and physical perturbation. Disclosed are methods, analytics, and their uses for reliable perfusion monitoring, arterial oxygen saturation monitoring, heart rate monitoring during daily activities and in hospital settings and for extraction of physiological parameters such as respiration information, hemodynamic parameters, venous capacity, and fluid responsiveness. The system and methods disclosed are extendable to include monitoring platforms for perfusion, hypoxia, arrhythmia detection, airway obstruction detection and sleep disorders including apnea.Board of Regents, University of Texas Syste
Can One Trust Quantum Simulators?
Various fundamental phenomena of strongly-correlated quantum systems such as
high- superconductivity, the fractional quantum-Hall effect, and quark
confinement are still awaiting a universally accepted explanation. The main
obstacle is the computational complexity of solving even the most simplified
theoretical models that are designed to capture the relevant quantum
correlations of the many-body system of interest. In his seminal 1982 paper
[Int. J. Theor. Phys. 21, 467], Richard Feynman suggested that such models
might be solved by "simulation" with a new type of computer whose constituent
parts are effectively governed by a desired quantum many-body dynamics.
Measurements on this engineered machine, now known as a "quantum simulator,"
would reveal some unknown or difficult to compute properties of a model of
interest. We argue that a useful quantum simulator must satisfy four
conditions: relevance, controllability, reliability, and efficiency. We review
the current state of the art of digital and analog quantum simulators. Whereas
so far the majority of the focus, both theoretically and experimentally, has
been on controllability of relevant models, we emphasize here the need for a
careful analysis of reliability and efficiency in the presence of
imperfections. We discuss how disorder and noise can impact these conditions,
and illustrate our concerns with novel numerical simulations of a paradigmatic
example: a disordered quantum spin chain governed by the Ising model in a
transverse magnetic field. We find that disorder can decrease the reliability
of an analog quantum simulator of this model, although large errors in local
observables are introduced only for strong levels of disorder. We conclude that
the answer to the question "Can we trust quantum simulators?" is... to some
extent.Comment: 20 pages. Minor changes with respect to version 2 (some additional
explanations, added references...
Automatic programming methodologies for electronic hardware fault monitoring
This paper presents three variants of Genetic Programming (GP) approaches for intelligent online performance monitoring of electronic circuits and systems. Reliability modeling of electronic circuits can be best performed by the Stressor - susceptibility interaction model. A circuit or a system is considered to be failed once the stressor has exceeded the susceptibility limits. For on-line prediction, validated stressor vectors may be obtained by direct measurements or sensors, which after pre-processing and standardization are fed into the GP models. Empirical results are compared with artificial neural networks trained using backpropagation algorithm and classification and regression trees. The performance of the proposed method is evaluated by comparing the experiment results with the actual failure model values. The developed model reveals that GP could play an important role for future fault monitoring systems.This research was supported by the International Joint Research Grant of the IITA (Institute of Information Technology Assessment) foreign professor invitation program of the MIC (Ministry of Information and Communication), Korea
Hybrid computer Monte-Carlo techniques
Hybrid analog-digital computer systems for Monte Carlo method application
The effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study
High-level brain function such as memory, classification or reasoning can be
realized by means of recurrent networks of simplified model neurons. Analog
neuromorphic hardware constitutes a fast and energy efficient substrate for the
implementation of such neural computing architectures in technical applications
and neuroscientific research. The functional performance of neural networks is
often critically dependent on the level of correlations in the neural activity.
In finite networks, correlations are typically inevitable due to shared
presynaptic input. Recent theoretical studies have shown that inhibitory
feedback, abundant in biological neural networks, can actively suppress these
shared-input correlations and thereby enable neurons to fire nearly
independently. For networks of spiking neurons, the decorrelating effect of
inhibitory feedback has so far been explicitly demonstrated only for
homogeneous networks of neurons with linear sub-threshold dynamics. Theory,
however, suggests that the effect is a general phenomenon, present in any
system with sufficient inhibitory feedback, irrespective of the details of the
network structure or the neuronal and synaptic properties. Here, we investigate
the effect of network heterogeneity on correlations in sparse, random networks
of inhibitory neurons with non-linear, conductance-based synapses. Emulations
of these networks on the analog neuromorphic hardware system Spikey allow us to
test the efficiency of decorrelation by inhibitory feedback in the presence of
hardware-specific heterogeneities. The configurability of the hardware
substrate enables us to modulate the extent of heterogeneity in a systematic
manner. We selectively study the effects of shared input and recurrent
connections on correlations in membrane potentials and spike trains. Our
results confirm ...Comment: 20 pages, 10 figures, supplement
Contour Detector and Data Acquisition System for the Left Ventricular Outline
A real-time contour detector and data acquisition system is described for an angiographic apparatus having a video scanner for converting an X-ray image of a structure characterized by a change in brightness level compared with its surrounding into video format and displaying the X-ray image in recurring video fields. The real-time contour detector and data acqusition system includes track and hold circuits; a reference level analog computer circuit; an analog compartor; a digital processor; a field memory; and a computer interface
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