• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.141-148
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• 2012

A design of a 32-bit fourth-stage decimation filter decimation filter used in sigma-delta analog-to-digital (A/D) converter is proposed in this work. A four-stage decimation filter with down-sampling factor of 512 and 32-bit output is developed. A multi-stage cascaded integrator-comb (CIC) filter, which reduces the sampling rate by 64, is used in the first stage. Three half-band FIR filters are used after the CIC filter, each of which reduces the sampling rate by two. The pipeline structure is applied in the CIC filter to reduce the power consumption of the CIC. The Canonic Signed Digit (CSD) arithmetic is used to optimize the multiplier structure of the FIR filter. This filter is implemented based on a semi-custom design flow and a 130nm CMOS standard cell library. This decimation filter operates at 98.304 MHz and provides 32-bit output data at an audio frequency of 192 kHz with power consumption of $697{\mu}W$. In comparison to the previous work, this design shows a higher performance in resolution, operation frequency and decimation factor with lower power consumption and small logic utilization.

• Proceedings of the IEEK Conference
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• 2004.06b
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• pp.533-536
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• 2004

In this paper, CMOS A/D converter with 10bit 32MSPS at 3.3V is designed for HPNA 2.0. In order to obtain the resolution of 10bit and the character of high-speed operation, we present multi-stage type architecture. That consist of sample and hold(S&H), 4bit flash ADC and 4bit Multiplier D/A Converter (MADC) also the Overflow and Underflow for timing error correct of Digital Correct ion Logic (DCL). The proposed ADC is based on 0.35um 3-poly 5-metal N-well CMOS technology. and it consumes 130mW at 3.3V power supply.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1627-1634
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• 2021

This paper introduces a low-power compact ADC circuit for analog Convolutional filter for low-power neural network accelerator SOC. While convolutional neural network accelerators can speed up the learning and inference process, they have drawback of consuming excessive power and occupying large chip area due to large number of multiply-and-accumulate operators when implemented in complex digital circuits. To overcome these drawbacks, we implemented an analog convolutional filter that consists of an analog multiply-and-accumulate arithmetic circuit along with an ADC. This paper is focused on the design optimization of a low-power 8bit SAR ADC for the analog convolutional filter accelerator We demonstrate how to minimize the capacitor-array DAC, an important component of SAR ADC, which is three times smaller than the conventional circuit. The proposed ADC has been fabricated in CMOS 65nm process. It achieves an overall size of 1355.7㎛², power consumption of 2.6㎼ at a frequency of 100MHz, SNDR of 44.19 dB, and ENOB of 7.04bit.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.497-500
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• 2005

This paper presents a design of a hybrid sensor chip which integrates an A/D converter module and a phase measurement module for measuring power line phase. Recursive sliding DFT based phase measurement module is designed using time shared multiplier which can reduce the size of SoC implementation. A/D converter is based on the sigma delta modulation in order to minimize the implementation space of the analog part and designed to obtain 8-bit resolution. Computer simulations and FPGA implementation are performed to verify hybrid sensor chip design. The hybrid sensor chip for 4-channel power line phase measurement is fabricated by using 0.35 micrometer CMOS process.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.186-192
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• 1996

A modified learning rule is introduced for the implementation of feedforward artificial neural networks with on-chip learning circuitry using standard analog CMOS technology. Learning rule, is modified form the EBP (error back propagation) rule which is one of the well-known learning rules for the feedforward rtificial neural nets(FANNs). The employed MEBP ( modified EBP) rule is well - suited for the hardware implementation of FANNs with on-chip learning rule. As a ynapse circuit, a four-quadrant vector-product linear multiplier is employed, whose input/output signals are given with voltage units. Two $2{\times}2{\times}1$ FANNs are implemented with the learning circuitry. The implemented FANN circuits have been simulatied with learning test patterns using the PSPICE circuit simulator and their results show correct learning functions.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.2 s.332
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• pp.23-30
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• 2005

This paper describes a DLL(delay locked loop)-based multi-clock generator having the lower active stand-by power as well as a fast relocking after re-activating the DLL. for low power and high speed VLSI chip. It enables a frequency multiplication using frequency multiplier scheme and produces output clocks with 50:50 duty-ratio regardless of the duty-ratio of system clock. Also, digital control scheme using DAC enables a fast relocking operation after exiting a standby-mode of the clock system which was obtained by storing analog locking information as digital codes in a register block. Also, for a clock multiplication, it has a feed-forward duty correction scheme using multiphase and phase mixing corrects a duty-error of system clock without requiring additional time. In this paper, the proposed DLL-based multi-clock generator can provides a synchronous clock to an external clock for I/O data communications and multiple clocks of slow and high speed operations for various IPs. The proposed DLL-based multi-clock generator was designed by the area of $1796{\mu}m\times654{\mu}m$ using $0.35-{\mu}m$ CMOS process and has $75MHz\~550MHz$ lock-range and maximum multiplication frequency of 800 MHz below 20psec static skew at 2.3v supply voltage.