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Neural network designing method and digital-to-analog fitting method
US9015095B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9015095-B2 |
| Application number | US-201213650928-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 12, 2012 |
| Priority date | Jan 25, 2012 |
| Publication date | Apr 21, 2015 |
| Grant date | Apr 21, 2015 |
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Abstract
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A neural network designing method forms a RNN (Recurrent Neural Network) circuit to include a plurality of oscillating RNN circuits configured to output natural oscillations, and an adding circuit configured to obtain a sum of outputs of the plurality of oscillating RNN circuits, and inputs discrete data to the plurality of oscillating RNN circuits in order to compute a fitting curve with respect to the discrete data output from the adding circuit.
First claim
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What is claimed is: 1. A neural network designing method comprising: a forming procedure causing a computer to form a RNN (Recurrent Neural Network) circuit to include a plurality of oscillating RNN circuits configured to output natural oscillations, and an adding circuit configured to obtain a sum of outputs of the plurality of oscillating RNN circuits; and a computing procedure causing the computer to input discrete data to the plurality of oscillating RNN circuits, in order to compute a fitting curve with respect to the discrete data output from the adding circuit, wherein the computing procedure includes computing and storing in a storage unit a 0 ,a 1 , . . . , a 2n-1 ,b 1 , . . . , b 2n-1 represented by the following formulas from the discrete data y 0 =0, y 1 , . . . , y 2n-1 , y 2n =0, a 0 = 1 2 n ∑ i = 1 2 n - 1 y i = 1 2 n ∑ i = 0 2 n y i a q = ψ ( q 2 n ) 4 n π 2 ∑ i = 1 2 n - 1 y i ( - cos ( i - 1 ) q π n + 2 cos i q π n - cos ( i + 1 ) q π n ) q = 1 , 2
Assignees
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Classifications
- G06N3/044Primary
Recurrent networks, e.g. Hopfield networks · CPC title
- G06N3/049Primary
Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs · CPC title
- G06N3/0445Primary
Physics · mapped topic
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- What does patent US9015095B2 cover?
- A neural network designing method forms a RNN (Recurrent Neural Network) circuit to include a plurality of oscillating RNN circuits configured to output natural oscillations, and an adding circuit configured to obtain a sum of outputs of the plurality of oscillating RNN circuits, and inputs discrete data to the plurality of oscillating RNN circuits in order to compute a fitting curve with respe…
- Who is the assignee on this patent?
- Fujitsu Ltd
- What technology area does this patent fall under?
- Primary CPC classification G06N3/044. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Apr 21 2015 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).