Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Andrew I, Hanna"'
Publikováno v:
PLoS Biology, Vol 8, Iss 11, p e1000537 (2010)
The mechanisms by which genes control organ shape are poorly understood. In principle, genes may control shape by modifying local rates and/or orientations of deformation. Distinguishing between these possibilities has been difficult because of inter
Externí odkaz:
https://doaj.org/article/09f253a585754cf5ad709a1428b316cc
Autor:
Danilo P. Mandic, Andrew I. Hanna
Publikováno v:
Journal of the Franklin Institute. 340:363-370
Nonlinear system identification and prediction is a complex task, and often non-parametric models such as neural networks are used in place of intricate mathematics. To that cause, recently an improved approach to nonlinear system identification usin
Autor:
Andrew I. Hanna, Danilo P. Mandic
Publikováno v:
Neural Networks. 16:155-159
A complex-valued nonlinear gradient descent (CNGD) learning algorithm for a simple finite impulse response (FIR) nonlinear neural adaptive filter with an adaptive amplitude of the complex activation function is proposed. This way the amplitude of the
Autor:
Enrico Coen, Nicolas B. Langlade, Sandra Bensmihen, José Luis Micol, Andrew Bangham, Andrew I. Hanna
Publikováno v:
HFSP Journal
HFSP Journal, 2008, 2 (2), pp.110-120. ⟨10.2976/1.2836738⟩
HFSP Journal, 2008, 2 (2), pp.110-120. ⟨10.2976/1.2836738⟩
A key approach to understanding how genes control growth and form is to analyze mutants in which shape and size have been perturbed. Although many mutants of this kind have been described in plants and animals, a general quantitative framework for de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d42f4eb82af057720656c8679b1346bc
https://hal.inrae.fr/hal-02666041
https://hal.inrae.fr/hal-02666041
Autor:
Andrew Bangham, Nicolas B. Langlade, Xianzhong Feng, Tracy Dransfield, Enrico Coen, Christophe Thébaud, Andrew Hudson, Lucy Copsey, Andrew I. Hanna
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America. 102(29)
Understanding evolutionary change requires phenotypic differences between organisms to be placed in a genetic context. However, there are few cases where it has been possible to define an appropriate genotypic space for a range of species. Here we ad
Publikováno v:
NNSP
A class of algorithms for training neural adaptive filters employed for nonlinear adaptive filtering is introduced. Sign algorithms incorporated with the fully adaptive normalised nonlinear gradient descent (SFANNGD) algorithm, normalised nonlinear g
Autor:
Andrew I, Hanna, Danilo P, Mandic
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 16(2)
A complex-valued nonlinear gradient descent (CNGD) learning algorithm for a simple finite impulse response (FIR) nonlinear neural adaptive filter with an adaptive amplitude of the complex activation function is proposed. This way the amplitude of the
Autor:
Danilo P. Mandic, Andrew I. Hanna
Publikováno v:
ICASSP
A backpropagation based algorithm for training nonlinear complex valued feed-forward neural networks employed as nonlinear adaptive filters is derived. The proposed normalised complex backpropagation (NCBP) algorithm is an improvement on the complex
Publikováno v:
ICASSP
An algorithm for training nonlinear adaptive finite impulse response (FIR) filters employed for nonlinear prediction and system identification is introduced. This general adaptive normalised nonlinear gradient descent (ANNGD) algorithm is fully gradi
Publikováno v:
PLoS Biology, Vol 8, Iss 11, p e1000537 (2010)
PLoS Biology
PLoS Biology
A combination of experimental analysis and mathematical modelling shows how the genetic control of tissue polarity plays a fundamental role in the development and evolution of form.
The mechanisms by which genes control organ shape are poorly un
The mechanisms by which genes control organ shape are poorly un