Search results for "Initialization"
showing 10 items of 55 documents
Statistical analysis of multilayer perceptrons performances
2002
The paper is based on a series of studies on the learning capabilities of multilayered perceptrons (MLP). The complexity of these nonlinear systems can be varied, acting for instance on the number of hidden units, but we will be confronted with a choice dilemma, concerning the optimal complexity of the system for a given problem. By the mean of statistical methods, we have found that the effective number of hidden units is smaller than the potential size; some units have a "binary" activation level or a time constant activation. We also prove that weight initialization to small values is recommended and reduce the effective size of the hidden layer.
Artificial driving cycles for the evaluation of energetic needs of electric vehicles
2012
International audience; This article presents a novel method to simulate artificial driving cycles that have the same significant characteristics as measured driving cycles. The driving cycles are based on only two different easily accessible parameters namely mean velocity and mean positive acceleration as well as their standard variations. Those parameters allow to adapt the driving cycles to different cycle types (urban, extra urban, highway), length and duration. Other than know drive cycle simulators, the approach is based on normal distribution of velocities and accelerations, thus needing to analyze only few cycles for the initialization.
Observation of individual spin quantum transitions of a single antiproton
2017
We report on the detection of individual spin quantum transitions of a single trapped antiproton in a Penning trap. The spin-state determination, which is based on the unambiguous detection of axial frequency shifts in presence of a strong magnetic bottle, reaches a fidelity of 92.1% . Spin-state initialization with >99.9% fidelity and an average initialization time of 24 min are demonstrated. This is a major step towards an antiproton magnetic moment measurement with a relative uncertainty on the part-per-billion level. We report on the detection of individual spin quantum transitions of a single trapped antiproton in a Penning trap. The spin-state determination, which is based on the unam…
Newton Method for Minimal Learning Machine
2021
Minimal Learning Machine (MLM) is a distance-based supervised machine learning method for classification and regression problems. Its main advances are simple formulation and fast learning. Computing the MLM prediction in regression requires a solution to the optimization problem, which is determined by the input and output distance matrix mappings. In this paper, we propose to use the Newton method for solving this optimization problem in multi-output regression and compare the performance of this algorithm with the most popular Levenberg–Marquardt method. According to our knowledge, MLM has not been previously studied in the context of multi-output regression in the literature. In additio…
A robust evolutionary algorithm for the recovery of rational Gielis curves
2013
International audience; Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot…
Teaching GP to program like a human software developer
2019
Program synthesis is one of the relevant applications of GP with a strong impact on new fields such as genetic improvement. In order for synthesized code to be used in real-world software, the structure of the programs created by GP must be maintainable. We can teach GP how real-world software is built by learning the relevant properties of mined human-coded software - which can be easily accessed through repository hosting services such as GitHub. So combining program synthesis and repository mining is a logical step. In this paper, we analyze if GP can write programs with properties similar to code produced by human software developers. First, we compare the structure of functions generat…
Universal decay cascade model for dynamic quantum dot initialization.
2009
Dynamic quantum dots can be formed by time-dependent electrostatic potentials in nanoelectronic devices, such as gate- or surface-acoustic-wave-driven electron pumps. Ability to control the number of captured electrons with high precision is required for applications in fundamental metrology and quantum information processing. In this work we propose and quantify a scheme to initialize quantum dots with a controllable number of electrons. It is based on the stochastic decrease in the electron number of a shrinking dynamic quantum dot and is described by a nuclear decay cascade model with "isotopes" being different charge states of the dot. Unlike the natural nuclei, the artificial confineme…
Centrality dependence of multiplicity, transverse energy, and elliptic flow from hydrodynamics
2001
The centrality dependence of the charged multiplicity, transverse energy, and elliptic flow coefficient is studied in a hydrodynamic model, using a variety of different initializations which model the initial energy or entropy production process as a hard or soft process, respectively. While the charged multiplicity depends strongly on the chosen initialization, the p_t-integrated elliptic flow for charged particles as a function of charged particle multiplicity and the p_t-differential elliptic flow for charged particles in minimum bias events turn out to be almost independent of the initial energy density profile.
Fast ion swapping for quantum-information processing
2016
We demonstrate a swap gate between laser-cooled ions in a segmented microtrap via fast physical swapping of the ion positions. This operation is used in conjunction with qubit initialization, manipulation, and readout and with other types of shuttling operations such as linear transport and crystal separation and merging. Combining these operations, we perform quantum process tomography of the swap gate, obtaining a mean process fidelity of 99.5(5)%. The swap operation is demonstrated with motional excitations below 0.05(1) quantum for all six collective modes of a two-ion crystal for a process duration of $42\ensuremath{\mu}\mathrm{s}$. Extending these techniques to three ions, we reverse …
Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography.
2019
Abstract In the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one slice of the tomographic dataset. The algorithm takes care of identifying an optimal and user-independent region of interest around the anomalous tissue and located on the slice containing the highest standardized uptake value so to start the successive segmentation task. The three-dimensional volume is then…