Information Theory: Data Processing Inequality, violation?

In summary, the speaker is wondering why adding noise to a speech signal and then high-pass filtering it can increase the mutual information, seemingly violating the data processing inequality. They suggest that the inequality may not apply due to the non-stationary nature of the input signal and its lack of being a Markov chain. They also reference the data processing inequality to clarify their question.
  • #1
dezeegt
1
0
Let's suppose I have a speech signal with frequency content >300 Hz. I then add noise to this signal, that happens to be somewhere below 300 Hz. I then high-pass filter the signal (300+ Hz) and I have increased the mutual information and seemingly violated the data processing inequality.

Can anyone explain why this can occur? I assume it's because the data processing inequality does not apply since the input signal is not stationary and it's probably not really a Markov chain...but I'm not sure.

Thanks!
 
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  • #2
By "data processing inequality" I guess you mean this: http://www.vis.caltech.edu/~zoltan/szeged4/img9.htm

By "increased the mutual information" I assume you mean, increased the mutual information between the signal and the output of the high-pass filter, by adding the noise. But the data processing inequality doesn't say the inclusion of R1 can't increase I(S, R2), it only says I(S,R1) > I(S,R2). There's no contradiction.
 
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Related to Information Theory: Data Processing Inequality, violation?

What is Information Theory?

Information Theory is a mathematical discipline that deals with the quantification, storage, and communication of information. It studies the fundamental limits of information processing and communication, and how to efficiently encode, transmit, and decode information.

What is Data Processing Inequality?

Data Processing Inequality is a fundamental principle in Information Theory which states that processing data cannot increase the amount of information in a system. In other words, the output of any data processing operation can only have less or equal information compared to the input.

How does Data Processing Inequality relate to Information Theory?

Data Processing Inequality is a key concept in Information Theory as it helps in understanding the limitations of data processing and communication systems. It is used to measure the efficiency and effectiveness of various data processing algorithms and techniques.

Can Data Processing Inequality be violated?

Yes, Data Processing Inequality can be violated in certain scenarios. This can happen when the data processing operation introduces new information, or when the input data is not fully utilized by the processing system. However, in most cases, the principle holds true and is a useful tool in information processing and communication.

How is Data Processing Inequality applied in real-world scenarios?

Data Processing Inequality has many practical applications, such as in data compression, error-correcting codes, and encryption. It is also used in fields like signal processing, computer science, and neuroscience to understand and improve data processing and communication systems.

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