Samsung electronics co., ltd. (20240319962). METHOD AND APPARATUS WITH DATA PROCESSING simplified abstract
Contents
METHOD AND APPARATUS WITH DATA PROCESSING
Organization Name
Inventor(s)
Ihor Vasyltsov of Suwon-si (KR)
Youngnam Hwang of Hwaseong-si (KR)
METHOD AND APPARATUS WITH DATA PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240319962 titled 'METHOD AND APPARATUS WITH DATA PROCESSING
The processor-implemented data processing method described in the abstract involves normalizing input data of an activation function that includes a division operation.
- Determining dividend data corresponding to the dividend of the division operation by reading a value from a memory addressed by a first lookup table using the normalized input data.
- Determining divisor data corresponding to the divisor of the division operation by accumulating the dividend data.
- Determining output data of the activation function corresponding to the output of the division operation obtained by reading a value from the memory addressed by a second lookup table using the dividend data and the divisor data.
Potential Applications: - This technology can be applied in various fields such as artificial intelligence, machine learning, and signal processing. - It can be used in developing advanced mathematical models and algorithms for data analysis.
Problems Solved: - Provides a method for efficiently processing data in activation functions that involve division operations. - Helps in improving the accuracy and speed of calculations in complex mathematical operations.
Benefits: - Enhances the performance of neural networks and deep learning algorithms. - Enables more precise and reliable data processing in computational tasks.
Commercial Applications: Title: Advanced Data Processing Method for Neural Networks This technology can be utilized in developing high-performance computing systems for data-intensive applications in industries such as finance, healthcare, and telecommunications. It can also be integrated into software tools for data analysis and pattern recognition.
Questions about the technology: 1. How does this data processing method improve the efficiency of activation functions in neural networks? 2. What are the potential implications of using this technology in real-time data processing systems?
Frequently Updated Research: Researchers are continuously exploring new ways to optimize data processing methods for neural networks and improve the performance of deep learning algorithms. Stay updated on the latest advancements in this field to leverage the benefits of cutting-edge technologies.
Original Abstract Submitted
a processor-implemented data processing method includes: normalizing input data of an activation function comprising a division operation; determining dividend data corresponding to a dividend of the division operation by reading, from a memory, a value of a first lookup table addressed by the normalized input data; determining divisor data corresponding to a divisor of the division operation by accumulating the dividend data; and determining output data of the activation function corresponding to an output of the division operation obtained by reading, from the memory, a value of a second lookup table addressed by the dividend data and the divisor data.
