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Tuliptrader

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Slade

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Thank you @Toto111 . All eyes on TDK
 
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Pappagolla

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Very interesting wrt TDK especially when considering the preventative maintenance video published on our website. Echoing The Castle once again it’s the vibe-rational analysis one.
 
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Hi @Toto111
This has all the signs of being significant. We need @Diogenese to do a deep patent dive into TDK to see what Ai they are using in this Edge sensor.

My opinion only DYOR
FF

AKIDA BALLISTA

I found this patent for TDK involving NN however I don’t have the expertise to interrogate it. I’ll leave that to DIO.


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United States Patent Application
20200371076
Kind Code
A1
Koenig; Matthias
November 26, 2020

Method and Apparatus for Operating a Multi-Gas Sensor

Abstract
A method and apparatus for operating a multi-gas sensor are disclosed. In an embodiment, a method includes providing at least one calibration input comprising sensor design data of the multi-gas sensor, which varies dependent on production process parameters, and/or sensor production process parameter data of the multi-gas sensor, and/or measurement results of the multi-gas sensor captured when the multi-gas sensor is exposed to one of the gases or a gas mixture to be detected and/or sensed by the multi-gas sensor; providing a trained neural network including an input layer with K input nodes, an output layer with L output nodes and at least one hidden layer; storing each calibration input as a fixed input to a corresponding input node of the trained neural network; and providing a multi-gas sensor output for at least a part of the gases to be detected and/or sensed by the multi-gas sensor dependent on the trained neural network and actual measured sensor values from the sensor elements.


Inventors:​
Koenig; Matthias; (Muenchen, DE)
Applicant:​
Name​
City​
State​
Country​
Type​

TDK Electronics AG

Munich

DE​
Family ID:​
73052967
Appl. No.:​
16/878167
Filed:​
May 19, 2020
 
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I found this patent for TDK involving NN however I don’t have the expertise to interrogate it. I’ll leave that to DIO.


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United States Patent Application
20200371076
Kind Code
A1
Koenig; Matthias
November 26, 2020

Method and Apparatus for Operating a Multi-Gas Sensor

Abstract
A method and apparatus for operating a multi-gas sensor are disclosed. In an embodiment, a method includes providing at least one calibration input comprising sensor design data of the multi-gas sensor, which varies dependent on production process parameters, and/or sensor production process parameter data of the multi-gas sensor, and/or measurement results of the multi-gas sensor captured when the multi-gas sensor is exposed to one of the gases or a gas mixture to be detected and/or sensed by the multi-gas sensor; providing a trained neural network including an input layer with K input nodes, an output layer with L output nodes and at least one hidden layer; storing each calibration input as a fixed input to a corresponding input node of the trained neural network; and providing a multi-gas sensor output for at least a part of the gases to be detected and/or sensed by the multi-gas sensor dependent on the trained neural network and actual measured sensor values from the sensor elements.


Inventors:​
Koenig; Matthias; (Muenchen, DE)
Applicant:​
Name​
City​
State​
Country​
Type​

TDK Electronics AG

Munich

DE​
Family ID:​
73052967
Appl. No.:​
16/878167
Filed:​
May 19, 2020
I’ll add this one in as well: Hopefully it’s useful.


CONTROLLER OF ARRAY INCLUDING NEUROMORPHIC ELEMENT, METHOD OF ARITHMETICALLY OPERATING DISCRETIZATION STEP SIZE, AND PROGRAM​

Feb 19, 2018 - TDK CORPORATION
A controller is a controller of an array including a neuromorphic element that multiplies a weight based on a value of a variable characteristic by a signal, and includes a control unit that controls the characteristic of the neuromorphic element by using a discretization step size obtained so that a predetermined condition for reducing an error or a predetermined condition for improving accuracy is satisfied on the basis of a case where a true value of the weight obtained with a higher accuracy than a resolution of the characteristic of the neuromorphic element is used and a case where a discretization step size which is set for the characteristic of the neuromorphic element is used.

:)
 
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Diogenese

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I found this patent for TDK involving NN however I don’t have the expertise to interrogate it. I’ll leave that to DIO.


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United States Patent Application
20200371076
Kind Code
A1
Koenig; Matthias
November 26, 2020

Method and Apparatus for Operating a Multi-Gas Sensor

Abstract
A method and apparatus for operating a multi-gas sensor are disclosed. In an embodiment, a method includes providing at least one calibration input comprising sensor design data of the multi-gas sensor, which varies dependent on production process parameters, and/or sensor production process parameter data of the multi-gas sensor, and/or measurement results of the multi-gas sensor captured when the multi-gas sensor is exposed to one of the gases or a gas mixture to be detected and/or sensed by the multi-gas sensor; providing a trained neural network including an input layer with K input nodes, an output layer with L output nodes and at least one hidden layer; storing each calibration input as a fixed input to a corresponding input node of the trained neural network; and providing a multi-gas sensor output for at least a part of the gases to be detected and/or sensed by the multi-gas sensor dependent on the trained neural network and actual measured sensor values from the sensor elements.


Inventors:​
Koenig; Matthias; (Muenchen, DE)
Applicant:​
Name​
City​
State​
Country​
Type​

TDK Electronics AG

Munich

DE​
Family ID:​
73052967
Appl. No.:​
16/878167
Filed:​
May 19, 2020
The input signals are the activations, the Calibration inputs are the weights.

The trick of this invention is to enable gas sensors to be calibrated from sampling only a few of the target gasses using a NN.

There is no description of an NPU, so the NN is one someone baked earlier.

US2020371076A1 Method and Apparatus for Operating a Multi-Gas Sensor

1656940325475.png


1656939481615.png


1 . A method for operating a multi-gas sensor comprising multiple sensor elements, wherein the multi-gas sensor is configured to detect and/or sense a predefined number M of different gases, the method comprising:

providing at least one calibration input comprising:

sensor design data of the multi-gas sensor, which varies dependent on production process parameters; and/or

sensor production process parameter data of the multi-gas sensor; and/or

measurement results of the multi-gas sensor captured when the multi-gas sensor is exposed to one of the gases or a gas mixture to be detected and/or sensed by the multi-gas sensor;

providing a trained neural network comprising an input layer with K input nodes, an output layer with L output nodes and at least one hidden layer, wherein L, M and K are natural numbers;

storing each calibration input as a fixed input to a corresponding input node of the trained neural network; and

providing a multi-gas sensor output for at least a part of the gases to be detected and/or sensed by the multi-gas sensor dependent on the trained neural network and actual measured sensor values from the sensor elements, which are provided to corresponding input nodes of the trained neural network.


[0030] The respective gas sensor element 10 shown in FIG. 1 comprises for example a sensing layer 11 of metal oxide. The gas sensor elements 10 are, for instance, integrated with a CMOS circuitry (not shown) on a single chip. A stack of layers 13 is arranged on a semiconductor substrate 14 required for the CMOS circuitry. The respective gas sensor element 10 comprises a membrane. A portion of the semiconductor substrate 14 is, for instance, etched away to form a cavity 12 at the location of the sensing layer 11 . Remaining layers 13 and possibly a remaining portion of the substrate 14 form a thin membrane to support the layer 11 .

[0031] The respective sensor element 10 comprises a heating element 15 . The heating element 15 is embedded within the layer 13 and comprises conducting elements. The heating element 15 is configured to provide a local source of heat to heat the metal oxide layer 11 e.g., during operation of the gas sensor element 10 . The temperature can rise rapidly around the metal oxide layer 11 on the membrane, while a thicker part of the gas sensor chip, i.e. the portion where the substrate 14 is not removed, reacts with a slower rise of temperature due to its thermal inertia. By controlling the heating element 15 accordingly, the metal oxide layer 11 can be activated for a measurement and be regenerated afterwards.

[0032] Each of the metal oxide layers 11 is contacted by two conductive electrodes and hence acts as a resistor. In the presence of a compound its resistance changes, thereby providing a measure of a concentration of the compound in the immediate vicinity of the metal oxide sensing layer 11 . The change of the resistance and/or impedance can be measured by a voltage measurement.

[0035] Gas sensors have to be calibrated. The output signals of the gas sensor elements 10 are generally in the form of a voltage value. Calibration is needed to implement a relation between the gas sensor element 10 signal and the concentration level of the corresponding gas.

[0038] Because of manufacturing tolerances it is not possible to produce exact copies of a gas sensor in a production process. There are always small fluctuations in the provided output signals. This is the reason why nearly all gas sensor products need to be calibrated after assembly. This means that calibration data is determined and used during operation of the gas sensor to adjust the sensor signals of the sensor elements 10 to provide accurate measurement output signals.

[0046] Embodiments provide relevant or most relevant calibration information and perform some gas exposure tests, i.e. not for all gases but only for some, and train the neural network N such that the neural network N can be used to provide the calibration also for other untested gases.
 
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Hi @Stable Genius
Probably wrong but having read both patents I think they are relying on a neuromorphic element that as @Diogenese would say was prepared earlier.

I will now wait for the Ogre to crush my hopes.

My opinion only DYOR
FF

AKIDA BALLISTA
Wow I got it right. 🤣😂🎉 FF
 
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Diogenese

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I’ll add this one in as well: Hopefully it’s useful.


CONTROLLER OF ARRAY INCLUDING NEUROMORPHIC ELEMENT, METHOD OF ARITHMETICALLY OPERATING DISCRETIZATION STEP SIZE, AND PROGRAM​

Feb 19, 2018 - TDK CORPORATION
A controller is a controller of an array including a neuromorphic element that multiplies a weight based on a value of a variable characteristic by a signal, and includes a control unit that controls the characteristic of the neuromorphic element by using a discretization step size obtained so that a predetermined condition for reducing an error or a predetermined condition for improving accuracy is satisfied on the basis of a case where a true value of the weight obtained with a higher accuracy than a resolution of the characteristic of the neuromorphic element is used and a case where a discretization step size which is set for the characteristic of the neuromorphic element is used.

:)
This is a method of correcting errors in analog neurons - again a pre-baked NPU.


1656941027191.png


1656941051838.png



[0006] As an example, Patent Literature 1 discloses a method of loading a weight (connection weight) obtained through real number value simulation into a circuit chip of a neural network including a discrete value synapse device in a spike-type neural network, and the circuit chip includes a neuromorphic element (see Patent Literature 1).

[0007] However, one problem occurring in a case where a neuromorphic element is applied to a neural network is a resolution of a resistance change. That is, a resistance of a neuromorphic element is not changed in a completely analog manner, but has discrete values like in a quantization step, and thus the use of a neuromorphic element in a neural network may result in the occurrence of a quantization error and deterioration of performance such as in identification.

[0008] For example, in a case where a neuromorphic element is used for a weight storage function and a weight updating function in a neural network, expressiveness of variables is insufficient as compared with a real-number-based simulation using a computer, and thus deterioration of identification performance or an increase in a period of time required until weight update function reaches convergence.


19 . An arithmetic operation method of arithmetically operating a discretization step size of a characteristic of a neuromorphic element for an array including the neuromorphic element that multiplies a weight based on a value of a variable characteristic by a signal, the arithmetic operation method comprising:

a step of arithmetically operating a true value of the weight with higher accuracy than a resolution of the characteristic of the neuromorphic element; and

a step of arithmetically operating a discretization step size so that a predetermined condition for reducing an error or a predetermined condition for improving accuracy is satisfied on the basis of a case where the true value of the weight is used and a case where the discretization step size which is set for the characteristic of the neuromorphic element is used.


1656941867587.png
 
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Diogenese

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Dallas

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Dallas

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‼️Explosiv☝
 
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Dallas

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Siemens, ich bin gerne Aktionär .AKIDA 🔥🔥🔥
 
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Dallas

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Sirod69

bavarian girl ;-)

TEACHING MACHINES
TO UNDERSTAND HUMANS

 
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cosors

👀
I don't expect royalty revenue in this 4c and possibly the next however I am expecting a significant increase in tech support revenue.
I theorise that royalty revenue in any future 4c's should be expected on the back of an increase in tech support revenue in prior 4c's.
I've thought about that too. A friend also mentioned that, who works for a really big company. He said it is perfectly normal to give something like that to R&D, that's what fixed funding pots are for. He's trying to do just that right now.
Screenshot_2022-07-04-21-56-07-57_40deb401b9ffe8e1df2f1cc5ba480b12.jpg

of course the right column
 
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stockduck

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Quite interessting to me, because of it is mentioned especially ARM..., Cadence...., Qualcomm and so on but not......Akida IP!
It doesn't have to mean anything, but it can mean anything, not to mention Akida IP?
What do you guys think?:unsure:

It was/is a light weight puff piece and means nothing as far as I am concerned.

My opinion only DYOR
FF

AKIDA BALLISTA
 
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