In 1942, Ralph Hartley proposed an analogue of the Fourier transform in his article "A More Symmetrical Fourier Analysis Applied to Transmission Problems". Just like Fourier transform (FT), Hartley transform (HT) turns the original signal into a sum of trigonometric functions. But there is one significant difference between them. FT converts real values to complex numbers, while HT provides only real results. Because of this difference, the Hartley transform did not become popular - scientists ...
In the previous articles, we started developing a multi-currency EA that works simultaneously with various trading strategies. The solution provided in the second article is already significantly different from the one presented in the first one. This indicates that we are still in search of the best options. Let's try to look at the developed system as a whole, abstracting from the small details of the implementation, in order to understand ways to improve it. To do this, let ...
In the previous article, we have thoroughly examined training via meta learner and cross-validation, as well as saving models in the ONNX format. I have also noted that machine learning models are not capable of finding patterns out of the box in disparate and contradictory data. In this case, it is very important what exactly is sent to the input and output of a neural network or any other machine learning algorithm. ... This article describes an attempt to understand ...
The proposed method is based on the Encoder-Decoder architecture. It was developed to solve problems of safe control of robotic systems. It allows the generation of sequences of trajectories for multiple agents consistent with the scene. AutoBots can predict the trajectory of one ego-agent or the distribution of future trajectories for all agents in the scene. In our case, we will try to apply the proposed model to generate sequences of price movements of currency pairs consistent with market dynamics. ...
The noise prediction module solves the auxiliary problem of identifying noise in the analyzed trajectories. This helps the movement prediction model better model potential spatial diversity and improves understanding of the underlying representation in movement prediction, thereby improving future predictions. The authors of the method conducted additional experiments to empirically demonstrate the critical importance of the spatial consistency and noise prediction modules for SSWNP. ...
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