We demonstrate the design of a neural network hardware, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Wei
OBJECT: DATA for all SOLVERS* Object: SOLVER • number of primary unknowns • solver properties • Object UNKNOWN UNKNOWN Object: UNKNOWN • ICs • BCs • element contribution • assemble function • number of degrees of freedom • nodal data *of linear or nonlinear type. View ...
Generalized linear models use linear methods to describe a potentially nonlinear relationship between predictor terms and a response variable.
These equations are identical in structure to the nonlinear version of the balance equations. 4. With the curvilinear vector balance equations derived above, the derivation of the linear shell balance equations is straightforward. Furthermore, such a parameterization of the equations is well suited for...
21, and linear state space vs nonlinear AR with radial basis function nonlinearities in ref. 22), which need not be the best representatives of linear and nonlinear models in general. While the compared linear and nonlinear models were found to be as predictive of EEG data in ref. 20 and ...
___ (Intercept) 1.0115 0.064275 15.737 8.4217e-56 x5 0.39508 0.066665 5.9263 3.0977e-09 x10 0.18863 0.05534 3.4085 0.0006532 x15 0.29295 0.053269 5.4995 3.8089e-08 100 observations, 96 error degrees of freedom Dispersion: 1 Chi^2-statistic vs. constant model: 91.7, p-value = 9.61e-20 stepwis...
under-actuated and nonlinear system and it is a challenge to control them, especially in case of aggressive maneuvers. Our goal in this project is to study the nonlinear geometric control approach to control a quadrotor. The configuration of the quadrotor system described on smooth nonlinear … ...
In future work, we aim to develop a nonlinear manifold based space–time ROM. Another interesting future direction is to build a component-wise space–time ROM as an extension to the work in [94], which is attractive for extreme-scale problems, whose simulation data are too big to store ...
=== There are some large data for which with/without nonlinear mappings gives similar performances. Without using kernels, one can efficiently train a much larger set via linear classification/regression. These data usually have a large number of features. Document classification is an example...
A focus on the modes of vibration (how the structure vibrates at specific frequencies) of the structure is given; this is called modal analysis. How to perform it is first introduced to have the basis to understand the linear and nonlinear techniques. A brief and nice introduction to modal ...