• Title/Summary/Keyword: CMOS neuron

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Implementation of Excitatory CMOS Neuron Oscillator for Robot Motion Control Unit

  • Lu, Jing;Yang, Jing;Kim, Yong-Bin;Ayers, Joseph;Kim, Kyung Ki
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.4
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    • pp.383-390
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    • 2014
  • This paper presents an excitatory CMOS neuron oscillator circuit design, which can synchronize two neuron-bursting patterns. The excitatory CMOS neuron oscillator is composed of CMOS neurons and CMOS excitatory synapses. And the neurons and synapses are connected into a close loop. The CMOS neuron is based on the Hindmarsh-Rose (HR) neuron model and excitatory synapse is based on the chemical synapse model. In order to fabricate using a 0.18 um CMOS standard process technology with 1.8V compatible transistors, both time and amplitude scaling of HR neuron model is adopted. This full-chip integration minimizes the power consumption and circuit size, which is ideal for motion control unit of the proposed bio-mimetic micro-robot. The experimental results demonstrate that the proposed excitatory CMOS neuron oscillator performs the expected waveforms with scaled time and amplitude. The active silicon area of the fabricated chip is $1.1mm^2$ including I/O pads.

CMOS Chaotic Neuron for Chaotic Neural Networks (카오스 신경망을 위한 CMOS 혼돈 뉴런)

  • 송한정;곽계달
    • Proceedings of the IEEK Conference
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    • 2000.11c
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    • pp.5-8
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    • 2000
  • Voltage mode chaotic neuron has been designed in integrated circuit and fabricated by using 0.8$\mu\textrm{m}$ single poly CMOS technology. The fabricated CMOS chaotic neuron consist of chaotic signal generator and sigmoid output function. This paper presents an analysis of the chaotic behavior in the voltage mode CMOS chaotic neuron. From empirical equations of the chaotic neuron, the dynamical responses such as time series, bifurcation, and average firing rate are calculated. And, results of experiments in the single chaotic neuron and chaotic neural networks by two neurons are shown and compared with the simulated results.

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Characterization and design guideline for neuron-MOSFET inverters (Neuron-MOSFET 인버터의 특성 분석 및 설계 가이드라인)

  • Kim, Sea-W.;Lee, Jae-K.;Park, Jong-T.;Jeong, Woon-D.
    • Journal of IKEEE
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    • v.3 no.2 s.5
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    • pp.161-167
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    • 1999
  • 3-input neuron-MOSFET inverters and 3-bit D/A converters using enhancement type device have been designed and fabricated by using standard 2-poly CMOS process. The voltage transfer curve and the noise margin of neuron-MOSFET inverters have been measured and characterized as the same method in normal CMOS inverters. From the theoretical calculation of the effects of coupling ratio on the voltage transfer curve and noise margin, we set up the design guideline for the gate oxide thickness and input gate layout in neuron-MOSFET inverters. BT using one of input gates as a control gate, we can design and fabricate the neuron-MOSFET D/A converter without offset voltage.

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CMOS neuron activation function (CMOS 뉴런의 활성화 함수)

  • Kang, Min-Jae;Kim, Ho-Chan;Song, Wang-Cheol;Lee, Sang-Joon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.627-634
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    • 2006
  • We have proposed the methods how to control the slope of CMOS inverter's characteristic and how to shift it in y axis. We control the MOS transistor threshold voltage for these methods. By observing that two transistors are in saturation region at the center of the CMOS inverter's characteristic, we have presented how to make the characteristic for one pole neuron. The circuit level simulation is used for verifying the proposed method. PSpice(OrCAD Co.) is used for circuit level simulation.

Design of a Neural Chip for Classifying Iris Flowers based on CMOS Analog Neurons

  • Choi, Yoon-Jin;Lee, Eun-Min;Jeong, Hang-Geun
    • Journal of Sensor Science and Technology
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    • v.28 no.5
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    • pp.284-288
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    • 2019
  • A calibration-free analog neuron circuit is proposed as a viable alternative to the power hungry digital neuron in implementing a deep neural network. The conventional analog neuron requires calibrations because a voltage-mode link is used between the soma and the synapse, which results in significant uncertainty in terms of current mapping. In this work, a current-mode link is used to establish a robust link between the soma and the synapse against the variations in the process and interconnection impedances. The increased hardware owing to the adoption of the current-mode link is estimated to be manageable because the number of neurons in each layer of the neural network is typically bounded. To demonstrate the utility of the proposed analog neuron, a simple neural network with $4{\times}7{\times}3$ architecture has been designed for classifying iris flowers. The chip is now under fabrication in 0.35 mm CMOS technology. Thus, the proposed true current-mode analog neuron can be a practical option in realizing power-efficient neural networks for edge computing.

Integrated Circuit Implementation and Characteristic Analysis of a CMOS Chaotic Neuron for Chaotic Neural Networks (카오스 신경망을 위한 CMOS 혼돈 뉴런의 집적회로 구현 및 특성 해석)

  • Song, Han-Jeong;Gwak, Gye-Dal
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.5
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    • pp.45-53
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    • 2000
  • This paper presents an analysis of the dynamical behavor in the chaotic neuron fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation models for the sigmoid output function and chaos generative block of the chaotic neuron are extracted from the measurement data. Then the dynamical responses of the chaotic neuron such as biurcation diagram, frequency responses, Lyapunov exponent, and average firing rate are calculated with numerical analysis. In addition, we construct the chaotic neural networks which are composed of two chaotic neurons with four synapses and obtain bifurcation diagram according to synaptic weight variation. And results of experiments in the single chaotic neuron and chaotic neural networks by two neurons with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.

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Design of a Silicon Neuron Circuit using a 0.18 ㎛ CMOS Process (0.18 ㎛ CMOS 공정을 이용한 실리콘 뉴런 회로 설계)

  • Han, Ye-Ji;Ji, Sung-Hyun;Yang, Hee-Sung;Lee, Soo-Hyun;Song, Han-Jung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.5
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    • pp.457-461
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    • 2014
  • Using $0.18{\mu}m$ CMOS process silicon neuron circuit of the pulse type for modeling biological neurons, were designed in the semiconductor integrated circuit. Neuron circuiSt providing is formed by MOS switch for initializing the input terminal of the capacitor to the input current signal, a pulse signal and an amplifier stage for generating an output voltage signal. Synapse circuit that can convert the current signal output of the input voltage signal, using a bump circuit consisting of NMOS transistors and PMOS few. Configure a chain of neurons for verification of the neuron model that provides synaptic neurons and two are connected in series, were performed SPICE simulation. Result of simulation, it was confirmed the normal operation of the synaptic transmission characteristics of the signal generation of nerve cells.

On the Implementation of the Digital Neuron Processor (디지탈 뉴런프로세서의 구현에 관한 연구)

  • 홍봉화;이지영
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.2
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    • pp.27-38
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    • 1999
  • This paper proposes a high speed digital neuron processor which uses the residue number system, making the high speed operation possible without carry propagation,. Consisting of the MAC(Multiplier and with Accumulator) operation unit, quotient operation unit and sigmoid function operation unit, the neuron processor is designed through 0.8$\mu$m CMOS fabrication. The result shows that the new implemented neuron processor can run at the speed of 19.2 nSec and the size can be reduced to 1/2 compared to the neuron processor implemented by the real number operation unit.

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Hardware implementation of a pulse-type neuron chain with a synapse function for hodgkin-huxley model (호지킨-헉슬리 모델을 위한 시냅스 기능을 지닌 신경세포 체인의 하드웨어 구현)

  • Jung, Jin-Woo;Kwon, Bo-Min;Park, Ju-Hong;Kim, Jin-Su;Lee, Je-Won;Park, Yong-Su;Song, Han-Jung
    • Journal of Sensor Science and Technology
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    • v.18 no.2
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    • pp.128-134
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    • 2009
  • Integrated circuit of a new neuron chain with a synapse function for Hodgkin-Huxley model which is a good electrical model about a real biological neuron is implemented in a $0.5{\mu}m$ 1 poly 2 metal CMOS technology. Pulse type neuron chain consist of series connected current controlled single neurons through synapses. For the realization of the single neuron, a pair of voltage mode oscillators using operational transconductance amplifiers and capacitors is used. The synapse block which is a connection element between neurons consist of a voltage-current conversion circuit using current mirror. SPICE simulation results of the proposed circuit show 160 mV amplitude pulse output and propagation of the signal through synapses. Measurements of the fabricated pulse type neuron chip in condition of ${\pm}2.5\;V$ power supply are shown and compared with the simulated results.

Integrated Circuit Implementation and Analysis of a Pulse-type Hodgkin-Huxley Neuron Model (펄스형 호지킨-혁슬리 신경세포 모델의 집적회로 구현 및 분석)

  • Kwon, Bo-Min;Jung, Jin-Woo;Park, Ju-Hong;Lee, Je-Won;Park, Yong-Su;Song, Han-Jung
    • 전자공학회논문지 IE
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    • v.46 no.1
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    • pp.16-22
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    • 2009
  • Integrated circuit of a pulse-type neuron for Hodgkin-Huxley model is implemented in a $0.5{\mu}m$ 1 poly 2 metal CMOS technology. Proposed pulse-type neuron model consist of input stage with summing function and pulse generating block which make neuron pulse above threshold value. Pulse generating circuit consist of several transistors, capacitors and negative resistor with a charge supply function. SPICE simulation results show that neuron pulse is generated above threshold current of 70 nA. Measurements of the fabricated pulse type neuron chip in condition of 5 V power supply are shown and compared with the simulated results.