منابع مشابه
From Spiking Neuron Models to Linear-Nonlinear Models
Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-line...
متن کاملThe Effects of Oil Price Movement on Nigerian Macroeconomic Variables: Evidence from Linear near and Nonlinear ARDL Modelling
T he study seeks to investigate both linear and nonlinear effects of oil price movement on critical macroeconomic variables (output, price and exchange rate) in Nigeria using ARDL modeling approach. Previous studies substantially relied on linear methods using VAR approach to unravel this links without a clear conclusion. In an attempt to seek better results in this study, we employ both l...
متن کاملLinear Models of Nonlinear Systems
Linear time-invariant approximations of nonlinear systems are used in many applications and can be obtained in several ways. For example, using system identification and the prediction-error method, it is always possible to estimate a linear model without considering the fact that the input and output measurements in many cases come from a nonlinear system. One of the main objectives of this th...
متن کاملComparison of Linear and Nonlinear Kinetic Models and Adsorption Isotherms of Zinc from an Aqueous Solution by Biochar
Fruits and citrus wastes are generated in the food industry in large quantities. Their management in Iran, as one of the major hubs of fruits and citrus production, is of great importance. In this study, the biochar samples were prepared from pomegranate, orange and lemon peel waste produced in a juice factory using the pyrolysis process in the range of 400-500 °C; then their efficiency for zin...
متن کاملNeural Decoding of Movements: From Linear to Nonlinear Trajectory Models
To date, the neural decoding of time-evolving physical state – for example, the path of a foraging rat or arm movements – has been largely carried out using linear trajectory models, primarily due to their computational efficiency. The possibility of better capturing the statistics of the movements using nonlinear trajectory models, thereby yielding more accurate decoded trajectories, is entici...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Mechanics: Theory and Experiment
سال: 2017
ISSN: 1742-5468
DOI: 10.1088/1742-5468/aa9335