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- Quantization (signal processing) - Wikipedia
An analog-to-digital converter (ADC) can be modeled as two processes: sampling and quantization Sampling converts a time-varying voltage signal into a discrete-time signal, a sequence of real numbers Quantization replaces each real number with an approximation from a finite set of discrete values
- What Is Quantization? | How It Works Applications
Learn how to explore and analyze the effects of quantization Resources include videos, examples, and documentation covering quantization
- Digital Communication - Quantization - Online Tutorials Library
Digital Communication Quantization - Learn about quantization in digital communication, including its importance, types, and effects on signal processing
- What is Quantization Sampling? Types Of Quantization | μ-Law A-Law
What Is Quantization? Quantization is the process of mapping continuous amplitude (analog) signal into discrete amplitude (digital) signal The analog signal is quantized into countable discrete levels known as quantization levels Each of these levels represents a fixed input amplitude
- What is Quantization? - IBM
Quantization is the process of reducing the precision of a digital signal, typically from a higher-precision format to a lower-precision format
- What is quantization in machine learning? - Cloudflare
In machine learning, quantization is a technique for making AI inference more efficient Learn how AI quantization and LLM quantization works
- What Is Quantization? Optimizing Data Compression - Coursera
Explore quantization and why it’s used to optimize large machine learning models Learn about how this technique might affect the speed, efficiency, accuracy, and resource requirements of your model
- What is Quantization? - Definition from Amazing Algorithms
Quantization is the process of converting a continuous signal (such as an analog audio or video signal) into a digital signal, which is represented as a series of discrete values This allows the signal to be processed, stored, and transmitted more efficiently
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