What is multi resolution analysis of signals

This step-by-step analysis method is called multi-resolution analysis, which is an important direction of wavelet transform in practical engineering applications. i is usually exponential, lognormal, normal, and gamma.

This series of approximations has different resolutions, hence the term multi-resolution analysis. Drawing on the pyramid algorithm, the continuous wavelet theory has been extended to the discrete domain. From the perspective of filter concept, the wavelet transform is to continuously filter the incoming signal f(t) with two sets of orthogonal high-pass and low-pass oscillators.

Source: An Image Coding Method with Controllable Distortion "Radio Communication Technology" 1997 Xu Peixia, Sun Gongxian.

Abstract: This paper proposes an image encoding method with selectable distortion based on wavelet transform and error feedback, which is suitable for remote database query and variable bitrate image hierarchical transmission. It decomposes the image to different resolutions through wavelet transform, and then uses the error feedback method to compensate step by step.

Since encoding errors at all pre-resolution are compensated, distortion-free images can be recovered.

This step-by-step analysis method is called multi-resolution analysis, which is an important direction of wavelet transform in practical engineering applications. i is usually exponential, lognormal, normal, gamma, etc.

Source: Wavelet and chaotic learning neural networks in short-term power load forecasting. Computer Engineering and Applications, 2003, Yanxi Yang, Ding Liu, Qi Li, Gang Zheng.

Abstract: This paper proposes a method for short-term load of power system using a hybrid model of wavelet and neural network. Firstly, based on the wavelet multi-resolution analysis method, the load sequence is decomposed into sequences with different frequency characteristics.

Then, according to the characteristics of each component after decomposition, different neural network models were constructed to carry out the first component separately. Compared with the traditional BP algorithm, the neural network algorithm adopts the chaotic learning algorithm, which uses the swimming nature of the chaotic orbit to enable the system to jump out of the constraints of local extremum and seek the global best advantage, which overcomes the essential problem of BP learning algorithm and can accelerate the network learning speed and improve the learning accuracy. Finally, the signal of each component is reconstructed to obtain the final result.

In the construction of the network model, the influence of climate factors is considered and used as a set of input points for the network. The experimental results show that the load** system based on this method has good accuracy and stability.

What is the multi-resolution analysis of the signal, the multi-resolution analysis of the signal is that it has a certain value for this resolution, but it depends on what the ratio is.

The size of the signal, because there are many times when the signal may be bad, or because there are many special reasons, so this can basically be distinguished.

For the analysis industry where you say what is the resolution of the signal, it's about clarity or not.