Exponential Negation of a Probability Distribution

Negation operation is important in intelligent information processing. Different with existing arithmetic negation, an exponential negation is presented in this paper. The new negation can be seen as a kind of geometry negation. Some basic properties of the proposed negation are investigated, we find that the fix point is the uniform probability distribution. The proposed exponential negation is an entropy increase operation and all the probability distributions will converge to the uniform distribution after multiple negation iterations. The convergence speed of the proposed negation is also faster than the existed negation. The number of iterations of convergence is inversely proportional to the number of elements in the distribution. Some numerical examples are used to illustrate the efficiency of the proposed negation.

The teaching reform of financial technology machine learning under the course group of intelligent information processing

Artificial intelligence is one of the most popular topics in today's era, and it is also an important development strategy of our country. In order to train high-level talents of artificial intelligence, the major of machine learning of financial science. China has gradually explored a set of relatively fixed teaching methods for the major of financial science and technology machine learning. However, in combination with the needs of the current era, industrial production puts forward higher requirements for the study of this major, It makes the traditional teaching method backward and unsuitable. In order to seek a more efficient teaching mode, it is urgent to reform the current teaching of financial technology machine learning. In this context, combined with the advanced teaching concept of intelligent information processing course group, this paper re plans the related courses of financial science and technology machine learning specialty, enhances the relevance between courses, enables the courses to connect and cooperate with each other, and forms a chain of excellent course group. strengthen the theoretical research, and strive to build a high-level teaching team to form a more three-dimensional and more close to the needs of the times. In order to investigate the rationality of the teaching reform, this paper carries on the verification analysis under the massive real data, obtains the reform method is scientific, is feasible through the analysis, and will play the positive role to the financial science and technology machine learning curriculum teaching reform under the intelligent information processing curriculum group.

Researching the fundamental principles of decision synthesis within technical systems of intelligent information processing

Работа посвящена концепции синтеза решения внутри компонентов технических систем интеллектуальной обработки информации. Разработана и реализована методология экспериментального исследования, направленного на обоснование научной и практической значимости данной концепции. В качестве объекта исследования использовалась компьютерная модель компонента принятия решения, обеспечивающего распознавание образа на основе данных, полученных о внешнем анализируемом объекте. Результаты исследования представляют собой отклик исследуемого компонента обработки информации на изменение внешних условий, влияющих на принимаемое решение. Выявлено, что инкорпорация механизмов синтеза решения в объект исследования способствовала появлению когнитивных свойств, проявляющихся в процессе обработки информации, что привело к повышению адаптационных способностей технической системы при изменении внешних условий её существования