106 research outputs found
Frequency conditions for the global stability of nonlinear delay equations with several equilibria
In our adjacent work, we developed a spectral comparison principle for
compound cocycles generated by delay equations. In particular, this principle
allows to derive frequency conditions (inequalities) for the uniform
exponential stability of such cocycles by means of their comparison with
stationary problems. Such inequalities are hard to verify analytically since
they contain resolvents of additive compound operators and to compute the
resolvents it is required solving a first-order PDEs with boundary conditions
involving both partial derivatives and delays.
In this work, we develop approximation schemes to verify some of the arising
frequency inequalities. Beside some general results, we mainly stick to the
case of scalar equations. By means of the Suarez-Schopf delayed oscillator and
the Mackey-Glass equations, we demonstrate applications of the theory to reveal
regions in the space of parameters where the absence of closed invariant
contours can be guaranteed. Since our conditions are robust, so close systems
also satisfy them, we expect them to actually imply the global stability, as in
known finite-dimensional results utilizing variants of the Closing Lemma which
is still awaiting developments in infinite dimensions
Double Refinement Network for Efficient Indoor Monocular Depth Estimation
Monocular depth estimation is the task of obtaining a measure of distance for
each pixel using a single image. It is an important problem in computer vision
and is usually solved using neural networks. Though recent works in this area
have shown significant improvement in accuracy, the state-of-the-art methods
tend to require massive amounts of memory and time to process an image. The
main purpose of this work is to improve the performance of the latest solutions
with no decrease in accuracy. To this end, we introduce the Double Refinement
Network architecture. The proposed method achieves state-of-the-art results on
the standard benchmark RGB-D dataset NYU Depth v2, while its frames per second
rate is significantly higher (up to 18 times speedup per image at batch size 1)
and the RAM usage per image is lower
Possibilities of use of industrial waste in road construction on the territory of the leningrad region
The main results of the joint international project №2006/123-438 “ECOROAD” (South-East Finland - Russia Neighborhood Programme) are presented in this paper. Coordinator of the project is Lappeenranta University of Technology, main partners are Saint-Petersburg State Polytechnical University and Saint Petersburg State Technological University of Plant Polymers. The project was implemented with support of the Committee of Natural Resources and Environmental Protection of the Leningrad Region, Committee of Road Maintenance and Transport of the Leningrad Region, and some enterprises of the Leningrad Region. Important data and recommendations for practical use of industrial waste of enterprises of the Leningrad Region (fly ashes, metallurgic slag, etc.) were received during implementation of the project
Relaxed Simultaneous Tomographic Reconstruction and Segmentation with Class Priors for Poisson Noise
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