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Evidence.
But you probably need to start by saying what you think quantization means.
Quantization is the process of converting a continuous signal into a discrete signal. This is done by mapping the continuous signal to a finite set of values. Quantization is used in a variety of applications, including digital signal processing, image processing, and machine learning.There are two main types of quantization:Uniform quantization: This is the simplest type of quantization, where the continuous signal is divided into equal intervals and each interval is mapped to a unique value.Non-uniform quantization: This type of quantization is used when the continuous signal has a non-uniform distribution. In this case, the intervals are sized differently to better represent the distribution of the signal.Quantization can be a lossy process, meaning that some information is lost in the conversion from a continuous signal to a discrete signal. However, the amount of information lost can be controlled by the number of quantization levels used. More quantization levels will result in less information loss, but will also require more storage space.Here are some examples of quantization:When you take a digital photo, the camera quantizes the continuous light signal into a discrete set of pixel values.When you encode an audio signal for MP3 playback, the audio signal is quantized to reduce the file size.When you train a machine learning model, the model's weights are quantized to reduce the model's size and improve its performance on embedded devices.Quantization is a powerful tool that can be used to improve the efficiency and performance of a variety of applications. However, it is important to understand the trade-offs involved in quantization before using it.
Quote from: alancalverd on 26/10/2023 22:35:23Use a calorimeter or photocell to determine E.I'm sure I heard about someone doing that.It gave the wrong answer.I think it's because they forgot about chemistry.
Use a calorimeter or photocell to determine E.
Then several labs built water calorimeters
Quote from: alancalverd on 27/10/2023 08:40:51Then several labs built water calorimetersWhat was the expected advantage of water calorimeters over the graphite?
Your pixels seem to be binary, whereas real camera pixels are linear.
Image size and intensity also affect the recorded image on the sensor.
Here it is. A closer look at sparkling water surface. //www.youtube.com/watch?v=wFvLxEqOeSM
Everything you see is entirely plausible. Not every explanatory hypothesis is plausible. That's science!
What needs explaining?
Anything that's seem unusual from a typical image reflected by water surface.
Do you have an explanatory hypothesis for the observation?
Anything that's seem unusual