604 research outputs found
Can Classical Noise Enhance Quantum Transmission?
A modified quantum teleportation protocol broadens the scope of the classical
forbidden-interval theorems for stochastic resonance. The fidelity measures
performance of quantum communication. The sender encodes the two classical bits
for quantum teleportation as weak bipolar subthreshold signals and sends them
over a noisy classical channel. Two forbidden-interval theorems provide a
necessary and sufficient condition for the occurrence of the nonmonotone
stochastic resonance effect in the fidelity of quantum teleportation. The
condition is that the noise mean must fall outside a forbidden interval related
to the detection threshold and signal value. An optimal amount of classical
noise benefits quantum communication when the sender transmits weak signals,
the receiver detects with a high threshold, and the noise mean lies outside the
forbidden interval. Theorems and simulations demonstrate that both
finite-variance and infinite-variance noise benefit the fidelity of quantum
teleportation.Comment: 11 pages, 3 figures, replaced with published version that includes
new section on imperfect entanglement and references to J. J. Ting's earlier
wor
Fuzzy models for fingerprint description
Fuzzy models, traditionally used in the control field to model controllers or plants behavior, are used in this work to describe fingerprint images. The textures, in this case the directions of the fingerprint ridges, are described for the whole image by fuzzy if-then rules whose antecedents consider a part of the image and the consequent is the associated dominant texture. This low-level fuzzy model allows extracting higher-level information about the fingerprint, such as the existence of fuzzy singular points and their fuzzy position within the image. This is exploited in two applications: to provide comprehensive information for user of unattended automatic recognition systems and to extract linguistic patterns to classify fingerprints
Expressing Measurement Uncertainty in OCL/UML Datatypes
Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to
be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, di cult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations de ned for the values of these types.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
On Vague Computers
Vagueness is something everyone is familiar with. In fact, most people think
that vagueness is closely related to language and exists only there. However,
vagueness is a property of the physical world. Quantum computers harness
superposition and entanglement to perform their computational tasks. Both
superposition and entanglement are vague processes. Thus quantum computers,
which process exact data without "exploiting" vagueness, are actually vague
computers
Probabilistic Quantum Memories
Typical address-oriented computer memories cannot recognize incomplete or
noisy information. Associative (content-addressable) memories solve this
problem but suffer from severe capacity shortages. I propose a model of a
quantum memory that solves both problems. The storage capacity is exponential
in the number of qbits and thus optimal. The retrieval mechanism for incomplete
or noisy inputs is probabilistic, with postselection of the measurement result.
The output is determined by a probability distribution on the memory which is
peaked around the stored patterns closest in Hamming distance to the input.Comment: Revised version to appear in Phys. Rev. Let
Quantum Forbidden-Interval Theorems for Stochastic Resonance
We extend the classical forbidden-interval theorems for a
stochastic-resonance noise benefit in a nonlinear system to a quantum-optical
communication model and a continuous-variable quantum key distribution model.
Each quantum forbidden-interval theorem gives a necessary and sufficient
condition that determines whether stochastic resonance occurs in quantum
communication of classical messages. The quantum theorems apply to any quantum
noise source that has finite variance or that comes from the family of
infinite-variance alpha-stable probability densities. Simulations show the
noise benefits for the basic quantum communication model and the
continuous-variable quantum key distribution model.Comment: 13 pages, 2 figure
A Cognitive Model of an Epistemic Community: Mapping the Dynamics of Shallow Lake Ecosystems
We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake
ecosystem model by augmenting the individual cognitive maps drawn by 8
scientists working in the area of shallow lake ecology. We calculated graph
theoretical indices of the individual cognitive maps and the collective
cognitive map produced by augmentation. The graph theoretical indices revealed
internal cycles showing non-linear dynamics in the shallow lake ecosystem. The
ecological processes were organized democratically without a top-down
hierarchical structure. The steady state condition of the generic model was a
characteristic turbid shallow lake ecosystem since there were no dynamic
environmental changes that could cause shifts between a turbid and a clearwater
state, and the generic model indicated that only a dynamic disturbance regime
could maintain the clearwater state. The model developed herein captured the
empirical behavior of shallow lakes, and contained the basic model of the
Alternative Stable States Theory. In addition, our model expanded the basic
model by quantifying the relative effects of connections and by extending it.
In our expanded model we ran 4 simulations: harvesting submerged plants,
nutrient reduction, fish removal without nutrient reduction, and
biomanipulation. Only biomanipulation, which included fish removal and nutrient
reduction, had the potential to shift the turbid state into clearwater state.
The structure and relationships in the generic model as well as the outcomes of
the management simulations were supported by actual field studies in shallow
lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to
understand the complex structure of shallow lake ecosystems as a whole and
obtain a valid generic model based on tacit knowledge of experts in the field.Comment: 24 pages, 5 Figure
Analysis of Bidirectional Associative Memory using SCSNA and Statistical Neurodynamics
Bidirectional associative memory (BAM) is a kind of an artificial neural
network used to memorize and retrieve heterogeneous pattern pairs. Many efforts
have been made to improve BAM from the the viewpoint of computer application,
and few theoretical studies have been done. We investigated the theoretical
characteristics of BAM using a framework of statistical-mechanical analysis. To
investigate the equilibrium state of BAM, we applied self-consistent signal to
noise analysis (SCSNA) and obtained a macroscopic parameter equations and
relative capacity. Moreover, to investigate not only the equilibrium state but
also the retrieval process of reaching the equilibrium state, we applied
statistical neurodynamics to the update rule of BAM and obtained evolution
equations for the macroscopic parameters. These evolution equations are
consistent with the results of SCSNA in the equilibrium state.Comment: 13 pages, 4 figure
Improved behavioral analysis of fuzzy cognitive map models
Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach. © Springer International Publishing AG, part of Springer Nature 2018.Peer reviewe
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Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller
In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques
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