Results 71 to 80 of about 116,745 (301)

Echinoderm‐Inspired Autonomy for Soft‐Legged Robots

Advanced Robotics Research, EarlyView.
Inspired by echinoderms, a modular soft robot achieves autonomous phototaxis without a central controller or explicit communication. Each limb independently adapts its actuation timing through local sensing and short‐term memory. Coordination emerges purely from physical interactions, demonstrating resilience to changes in morphology, environment, and ...
Harmannus A. H. Schomaker, Jelle de Vries, Johannes T. B. overvelde   +2 more
wiley   +1 more source

The Heston stochastic volatility model in Hilbert space

, 2017
We extend the Heston stochastic volatility model to a Hilbert space framework. The tensor Heston stochastic variance process is defined as a tensor product of a Hilbert-valued Ornstein-Uhlenbeck process with itself. The volatility process is then defined
Benth, Fred Espen, Simonsen, Iben Cathrine   +1 more
core   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

Advanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee, Oliver James, Gaeun Jung, Doyun Lee, Yee‐Joon Kim   +4 more
wiley   +1 more source

Spatial‐Wavelength Multiplexing Error‐Controlled Photonic Analog Computing System

Advanced Science, EarlyView.
A novel photonic integrated circuit prototype implementing the concept of general‐purpose analog computing and demonstrate its capability in radio frequency applications. The chip features a multichannel architecture and performs fully optical analog computation with frequency‐domain parallel processing. An FPGA‐based error‐correction algorithm aims to
Tao Zhu, Bowen Zhu, Shicheng Zhang, Keren Li, Xianchen Wu, Yazhi Pi, Jie Yan, Daigao Chen, Bingli Guo, Xi Xiao, Lei Wang, Xiaochuan Xu, Xuwei Xue, Shanguo Huang, Zizheng Cao, Shaohua Yu   +15 more
wiley   +1 more source

Complete–market models of stochastic volatility [PDF]

Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

Low Power Optoelectronic Neuromorphic Memristor for In‐Sensor Computing and Multilevel Hardware Security Communications

Advanced Science, EarlyView.
ABSTRACT Conventional software‐based encryption faces mounting limitations in power efficiency and security, inspiring the development of emerging neuromorphic computing hardware encryption. This study presents a hardware‐level multi‐dimensional encryption paradigm utilizing optoelectronic neuromorphic devices with low energy consumption of 3.3 fJ ...
Bo Sun, Jinhao Zhang, Jialin Meng, Tianyu Wang   +3 more
wiley   +1 more source

"Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio" [PDF]

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986,1994) and Nelson (1990).
Racicot, François-Éric, Théoret, Raymond   +1 more
core   +4 more sources

Markov Regime Switching of Stochastic Volatility Lévy Model on Approximation Mode

Journal of Applied Mathematics, 2013
This paper deals with financial modeling to describe the behavior of asset returns, through consideration of economic cycles together with the stylized empirical features of asset returns such as fat tails.
Arthit Intarasit
doaj   +1 more source

Bayesian Inference in a Stochastic Volatility Nelson-Siegel Model [PDF]

In this paper, we develop and apply Bayesian inference for an extended Nelson- Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the ...
Fuyu Yang, Nikolaus Hautsch
core  

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source