NUR Home
→
01.NU Schools
→
School of Engineering and Digital Sciences
→
Theses and Dissertations
→
Browsing Theses and Dissertations by Subject

Browsing Theses and Dissertations by Subject "AI"

Now showing items 1-5 of 5

BALANCING OF PERSONAL AND GROUP GOALS FOR AGENTS USING MULTI-AGENT REINFORCEMENT LEARNING

Zhabinets, Maxim (Nazarbayev University School of Engineering and Digital Sciences, 2022-04)

The number of AI agents in the world is increasing every day and they will need to interact with each other. It is in humanity’s best interest to teach these agents to respect the goals of others and live in harmony. In ...
HACKING NEURAL NETWORKS

Sharipov, Rollan (Nazarbayev University School of Engineering and Digital Sciences, 2021-10)

Today the amount of applications which use Neural Networks is increasing every day. The scope of use of such applications varies in different spheres such as medicine, economy, education and other fields. The main purpose ...
RECEIVER ARCHITECTURES AND ALGORITHMS FOR NON-ORTHOGONAL MULTIPLE ACCESS

Manglayev, Talgat (Nazarbayev University School of Engineering and Digital Sciences, 2020-05)

Multiple access (MA) schemes in cellular systems aim to provide high throughput to multiple users simultaneously while utilising the network resources efficiently. Traditionally, each user in the network is assigned a ...
SPEECH EMOTION RECOGNITION USING DEEP NEURAL NETWORKS

Mustazhapov, Raiymbek (Nazarbayev University School of Engineering and Digital Sciences, 2021-07)

There is an apparent evolving interest in speech emotion recognition (SER), one of the particular cases of a broader problem of multimedia pattern recognition. SER is considered to possess the capability to enhance the ...
TRANSFORMER FAULT PROGNOSIS USING VIBRATION SIGNALS AND FORECASTING TECHNIQUES

Kural, Askat (Nazarbayev University School of Engineering and Digital Sciences, 2022-05)

Vibration signature analysis is considered as an advanced and economical methods to evaluate transformer operating condition and mechanical integrity. Transformer condition monitoring and fault prognosis have been investigated ...