18505787. SIGMA-DELTA MODULATOR, ADC USED TO READ INFORMATION OF RESISTIVE MEMORY USING THE SIGMA-DELTA MODULATOR, AND DEEP LEARNING NEURAL NETWORK COMPUTING SYSTEM INCLUDING THE ADC simplified abstract (SK hynix Inc.)
SIGMA-DELTA MODULATOR, ADC USED TO READ INFORMATION OF RESISTIVE MEMORY USING THE SIGMA-DELTA MODULATOR, AND DEEP LEARNING NEURAL NETWORK COMPUTING SYSTEM INCLUDING THE ADC
Organization Name
Inventor(s)
Chang Yeop Lee of Daejeon (KR)
Jun Ho Cheon of Icheon-si (KR)
Woo Yeong Cho of Icheon-si (KR)
SIGMA-DELTA MODULATOR, ADC USED TO READ INFORMATION OF RESISTIVE MEMORY USING THE SIGMA-DELTA MODULATOR, AND DEEP LEARNING NEURAL NETWORK COMPUTING SYSTEM INCLUDING THE ADC - A simplified explanation of the abstract
This abstract first appeared for US patent application 18505787 titled 'SIGMA-DELTA MODULATOR, ADC USED TO READ INFORMATION OF RESISTIVE MEMORY USING THE SIGMA-DELTA MODULATOR, AND DEEP LEARNING NEURAL NETWORK COMPUTING SYSTEM INCLUDING THE ADC
Simplified Explanation: The patent application describes a sigma-delta modulator that converts a current signal into digital data, an ADC utilizing the modulator, and a neural network computing system using the ADC.
Key Features and Innovation:
- Sigma-delta modulator directly converts current signal into digital data.
- ADC minimizes noise generation and increases signal processing speed.
- Integration circuit generates integration current by integrating differential current.
- Quantization circuit generates digital modulation signal corresponding to integration current.
Potential Applications: The technology can be used in various applications such as data acquisition systems, sensor interfaces, and communication systems.
Problems Solved: The technology addresses the challenges of noise generation and signal processing speed in current signal conversion.
Benefits:
- Minimized noise generation
- Increased signal processing speed
- Efficient conversion of current signals into digital data
Commercial Applications: Potential commercial applications include IoT devices, medical devices, and industrial automation systems.
Prior Art: Readers can explore prior art related to sigma-delta modulators, ADCs, and neural network computing systems in relevant research papers and patents.
Frequently Updated Research: Stay updated on advancements in sigma-delta modulation, ADC technology, and neural network computing for potential improvements and applications.
Questions about Sigma-Delta Modulators: 1. How does the integration circuit in a sigma-delta modulator work? 2. What are the key advantages of using a sigma-delta modulator in ADCs?
Original Abstract Submitted
Disclosed are a sigma-delta modulator that directly converts a current signal into digital data, an ADC utilizing the sigma-delta modulator, and a neural network computing system utilizing the ADC. The sigma-delta modulator includes: a delta circuit to generate a differential current between an analog current signal output from a resistive memory and a first current included in the analog current signal, the first current having an amount of current determined by a digital modulation signal; an integration circuit to generate an integration current by integrating the differential current; and a quantization circuit to generate the digital modulation signal corresponding to the integration current. The sigma-delta modulator can minimize the generation of noise by using no capacitor that performs a function by a switch, and can increase a signal processing speed for conversion by allowing the signal processing speed to be determined by a signal processing speed of one element.
