2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE)
With the advent of QR readers and mobile phones the use of graphical codes like QR codes and data... more With the advent of QR readers and mobile phones the use of graphical codes like QR codes and data matrix code has become very popular. Despite the noise like appearance, it has the advantage of high data capacity, damage resistance and fast decoding robustness. The proposed system embeds the image chosen by the user to develop visually appealing QR codes with improved decoding robustness using BCH algorithm. The QR information bits are encoded into luminance value of the input image. The developed Picode can inspire perceptivity in multimedia applications and can ensure data security for instances like online payments. The system is implemented on Matlab and ARM cortex A8.
2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017
Nowadays in many commercial applications machine readable 2D barcode is being used. Conventional ... more Nowadays in many commercial applications machine readable 2D barcode is being used. Conventional QR codes comprises of random textures which fails to incorporate images preferred by the users. In the proposed system Noise like appearance of conventional QR code is substituted by a 2D barcode with greater data capacity maintaining both the novel appearance of the embedded image and correctness of the decoded message. The QR information bits are encoded into luminance value of the input image. Applying BCH Source channel error correction technique a new decoding scheme has been developed which enables a robust error correction performance as compared to the traditional 2D barcodes. Further the proposed QR code can inspire more perceptivity in multimedia applications and can ensure data security for instances like online payments. The system is implemented on Matlab and ARM cortex A8.
Vision compressive sensing, brain machine reference commands, and adaptive controller have been e... more Vision compressive sensing, brain machine reference commands, and adaptive controller have been effectively integrated that enable the robot to perform manipulation tasks as guided by human operator’s mind and according to its innovative views. The ideology proposed consists of following main phases: (1) action recognition (2) hardware interfacing. Initially action recognition captures video according to movements enacted in recognition system. Later, in hardware interfacing it passes required commands by a sensor attached to microcontroller that senses the input, detects where the arm to be moved and provides better accuracy for the movements to be performed. Thus this system maintains robust communication that can manipulate actions and cognitive emotions. In IoT, the server will upload data to client with the help of MQTT protocol to access robot from anywhere across the world. Cite this Article Zaiba, Ambika Sekhar. Human Robot Interface and Visual Compressive Detecting on Robot...
2009 4th IEEE Conference on Industrial Electronics and Applications, 2009
This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation func... more This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation function (NAF) and derivative of neuron activation function (DNAF) with programmable characteristics. NAF represents output of a single neuron. DNAF is needed in the training phase of neural networks. This circuit uses only FGMOSFETs to realize the NAF and DNAF. This circuit is designed to operate both in
2009 4th IEEE Conference on Industrial Electronics and Applications, 2009
Abstract— This paper presents an Operational Transconductance Amplifier realized using Floating G... more Abstract— This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFETs only. This can be used as Neuron Activation Function with wide linear range and adaptable threshold level and slope. This circuit is suitable for analog signal ...
This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFET... more This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFETs only. This can be used as Neuron Activation Function with wide linear range and adaptable threshold level and slope. This circuit is suitable for analog signal processing and neural network applications. This circuit generates log sigmoid and tan sigmoid NAF functions simultaneously. In this circuit the parameters of NAF function can be easily changed by changing voltage at the control gate of FGMOSFET. The linear range of the proposed FGMOSFET based OTA circuit is large and is equal to 2 V with a power supply of +0.75 V. Power analysis and noise analysis of the proposed circuit is performed. Mismatch study is performed using Monte Carlo simulation. TSPICE simulation results using 2 mum N-well process are presented. Layout design of the circuit is done using L-Edit in Tanner Tool.
This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation func... more This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation function (NAF) and derivative of neuron activation function (DNAF) with programmable characteristics. NAF represents output of a single neuron. DNAF is needed in the training phase of neural networks. This circuit uses only FGMOSFETs to realize the NAF and DNAF. This circuit is designed to operate both in saturation region and sub-threshold region. The performance of this circuit is compared with that of CMOS based NAF DNAF circuit. The comparative study includes linear range, temperature dependence, power dissipation, supply voltage and output resistance. The simulations are done using the tanner tool. The layout of the circuit is also presented. This paper also presents analytical study of proposed circuit and FGMOSFET current mirror in saturation region.
2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE)
With the advent of QR readers and mobile phones the use of graphical codes like QR codes and data... more With the advent of QR readers and mobile phones the use of graphical codes like QR codes and data matrix code has become very popular. Despite the noise like appearance, it has the advantage of high data capacity, damage resistance and fast decoding robustness. The proposed system embeds the image chosen by the user to develop visually appealing QR codes with improved decoding robustness using BCH algorithm. The QR information bits are encoded into luminance value of the input image. The developed Picode can inspire perceptivity in multimedia applications and can ensure data security for instances like online payments. The system is implemented on Matlab and ARM cortex A8.
2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017
Nowadays in many commercial applications machine readable 2D barcode is being used. Conventional ... more Nowadays in many commercial applications machine readable 2D barcode is being used. Conventional QR codes comprises of random textures which fails to incorporate images preferred by the users. In the proposed system Noise like appearance of conventional QR code is substituted by a 2D barcode with greater data capacity maintaining both the novel appearance of the embedded image and correctness of the decoded message. The QR information bits are encoded into luminance value of the input image. Applying BCH Source channel error correction technique a new decoding scheme has been developed which enables a robust error correction performance as compared to the traditional 2D barcodes. Further the proposed QR code can inspire more perceptivity in multimedia applications and can ensure data security for instances like online payments. The system is implemented on Matlab and ARM cortex A8.
Vision compressive sensing, brain machine reference commands, and adaptive controller have been e... more Vision compressive sensing, brain machine reference commands, and adaptive controller have been effectively integrated that enable the robot to perform manipulation tasks as guided by human operator’s mind and according to its innovative views. The ideology proposed consists of following main phases: (1) action recognition (2) hardware interfacing. Initially action recognition captures video according to movements enacted in recognition system. Later, in hardware interfacing it passes required commands by a sensor attached to microcontroller that senses the input, detects where the arm to be moved and provides better accuracy for the movements to be performed. Thus this system maintains robust communication that can manipulate actions and cognitive emotions. In IoT, the server will upload data to client with the help of MQTT protocol to access robot from anywhere across the world. Cite this Article Zaiba, Ambika Sekhar. Human Robot Interface and Visual Compressive Detecting on Robot...
2009 4th IEEE Conference on Industrial Electronics and Applications, 2009
This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation func... more This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation function (NAF) and derivative of neuron activation function (DNAF) with programmable characteristics. NAF represents output of a single neuron. DNAF is needed in the training phase of neural networks. This circuit uses only FGMOSFETs to realize the NAF and DNAF. This circuit is designed to operate both in
2009 4th IEEE Conference on Industrial Electronics and Applications, 2009
Abstract— This paper presents an Operational Transconductance Amplifier realized using Floating G... more Abstract— This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFETs only. This can be used as Neuron Activation Function with wide linear range and adaptable threshold level and slope. This circuit is suitable for analog signal ...
This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFET... more This paper presents an Operational Transconductance Amplifier realized using Floating Gate MOSFETs only. This can be used as Neuron Activation Function with wide linear range and adaptable threshold level and slope. This circuit is suitable for analog signal processing and neural network applications. This circuit generates log sigmoid and tan sigmoid NAF functions simultaneously. In this circuit the parameters of NAF function can be easily changed by changing voltage at the control gate of FGMOSFET. The linear range of the proposed FGMOSFET based OTA circuit is large and is equal to 2 V with a power supply of +0.75 V. Power analysis and noise analysis of the proposed circuit is performed. Mismatch study is performed using Monte Carlo simulation. TSPICE simulation results using 2 mum N-well process are presented. Layout design of the circuit is done using L-Edit in Tanner Tool.
This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation func... more This paper presents floating gate MOSFET (FGMOSFET) circuit for generating neuron activation function (NAF) and derivative of neuron activation function (DNAF) with programmable characteristics. NAF represents output of a single neuron. DNAF is needed in the training phase of neural networks. This circuit uses only FGMOSFETs to realize the NAF and DNAF. This circuit is designed to operate both in saturation region and sub-threshold region. The performance of this circuit is compared with that of CMOS based NAF DNAF circuit. The comparative study includes linear range, temperature dependence, power dissipation, supply voltage and output resistance. The simulations are done using the tanner tool. The layout of the circuit is also presented. This paper also presents analytical study of proposed circuit and FGMOSFET current mirror in saturation region.
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