Seite - 79 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Bild der Seite - 79 -
Text der Seite - 79 -
3.3. Black-boxModeling
Definition Interpretation
Nl Numberofnodes in the l-th
hiddenlayer (1≤ l≤L)
xli(k) Outputof the i-thnode in the l-th
layerat timek
zl+1j (k) = ∑Nl
i=1w l
j,i(k) ·xli(k) Inputof the j-thnode in the
(l+1)-th layerat timek
δlj(k) = ∂JOL(k)
∂zlj(k) Localgradientof the j-thnode in
the l-th layerat timek
fo, f ′
o(z) := df′o
dz Activationfunctionusedin the
output layeranditsfirst
derivative
g, g′(z) := dg ′
dz Activationfunctionusedin the
hiddenlayersanditsfirst
derivative
Table3.3. Parametersusedin theupdateofweights (inNN).
ThevaluesYNN,i(k)andYd,i(k)arethe i-thelementfromthevector
YNN(k)andYd(k), respectively.
For the l-th hidden layer (1≤ l≤L), the corresponding local gra-
dientvector is [Hay98][
δl(k) ]
= [
δl1(k), δ l
2(k), . . . δ l
Nl (k) ]
, (3.80)
where theelement isdefinedas
δli(k) = g ′(zli(k)) · Nl+1∑
j=1 δl+1j (k)w l+1
j,i (k−1), 1≤ i≤Nl. (3.81)
79
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
- Titel
- Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
- Autor
- Yiming Sun
- Verlag
- KIT Scientific Publishing
- Ort
- Karlsruhe
- Datum
- 2016
- Sprache
- englisch
- Lizenz
- CC BY-SA 3.0
- ISBN
- 978-3-7315-0467-2
- Abmessungen
- 14.8 x 21.0 cm
- Seiten
- 260
- Schlagwörter
- Mikrowellenerwärmung, Mehrgrößenregelung, Modellprädiktive Regelung, Künstliches neuronales Netz, Bestärkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
- Kategorie
- Technik