This piece of work deals with a philosophy of design adaptive controller, which is based on knowledge of mathematical model controlled plant. This master thesis is focused on closed-loop on-line parametric identification methods. An estimation of model´s parametres is solved by two main concepts: recursive leastsquare algorithms and neural estimators. In case of least-squares algorithm the strategy of preventing the typical problems are solved here. For instance numerical stability, accurecy and restricted forgetting. Back Propagation and Marquardt- Levenberg algorithm were choosen to represent artificial inteligence. There is still a little supermacy on the side of methods based on least-squares algorithm. To compare individual algorithms the grafical interface in MATLAB/Simulink was created.

This thesis deals with new teaching software, which supports asymmetric encryption algorithms based on the issue of large numbers´ factorization. A model program was created. It allows to carry out operations related to encryption and decryption with an interactive control. There is a simple way to understand the principle of the RSA encryption method with its help. The encryption of algorithms is generally analysed in chapters 1,2. Chapters 3 and 4 deals with RSA encryption algorithm in much more details, and it also describes the principles of the acquisition, management and usage of encryption keys. Chapters 5 suggest choosing of appropriate technologies for the creation of the final software product, which allow an appropriate way to present the characteristics of the extended RSA encryption algorithm. The final software product is the java applet. Aplet is described in the chaprers 6 and 7. It is divided into a theoretical and practical part. The theoretical part presents general information about the RSA encryption algorithm. The practical part allows the users of the program to have a try at tasks connected with the RSA algorthm in their own computers. The last part of Java applet deals with the users´ work results. The information obtained by the user in the various sections of the program are satisfactory enough to understand the principle of this algorithm´s operations.

Asymmetric cryptography uses two keys for encryption public key and for decryption private key. The asymmetric cryptosystems include RSA, ElGamal, Elliptic Curves and others. Generally, asymmetric cryptography is mainly used for secure short messages and transmission encryption key for symmetric cryptography. The thesis deals with these systems and implements selected systems (RSA, ElGamal, McEliece, elliptic curves and NTRU) into the application. The application can test the features of chosen cryptosystems. These systems and their performance are compared and evaluated with the measured values. These results can predict the future usage of these systems in modern informatics systems.

This thesis deals with the field of recommendation systems using deep neural networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advanced techniques based on machine learning. The core of the thesis is to use convolutional neural networks for natural language processing and create a hybrid book recommendation system. Suggested system includes matrix factorization and make recommendation based on user ratings and book metadata, including texts descriptions. I designed two models, one with bag-of-words technique and one with convolutional neural network. Both of them defeat baseline methods. On the created data set, that was created from the Goodreads, model with CNN beats model with BOW.

This thesis deals with the field of Recommendation systems using Deep Neural Networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advancec techniques based on machine learning.. The core of the thesis is the use of convolutional neural networks for natural language processing and the creation of a book recommendation system. Suggested system make recommendation based on user data, including user reviews and book data, including full texts.