![]() Learn about singular value decomposition as the solution to the generic MIMO problem. Objective: Understand different MIMO techniques, namely beamforming and spatial multiplexing. 5G frame structure: carriers and bandwidth parts.Objective: Learn about the resource grid and frame structure and numerology of 5G waveforms. Windowing to reduce out of band emissions.Generation of OFDM symbols using the IFFT.Motivation for multi-carrier vs single-carrier.Objective: Understand the basics of OFDM modulation, cyclic prefix insertion, and windowing. Understand general use cases and requirements for 5G. Other product or brand names may be trademarks or registered trademarks of their respective holders.Objective: Receive an introduction to the 5G standard and its differences from the LTE standard. See /trademarks for a list of additional trademarks. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. Founded in 1984, MathWorks employs more than 5000 people in 16 countries, with headquarters in Natick, Massachusetts, USA. ![]() MATLAB and Simulink are also fundamental teaching and research tools in the world's universities and learning institutions. Engineers and scientists worldwide rely on these product families to accelerate the pace of discovery, innovation, and development in automotive, aerospace, electronics, financial services, biotech-pharmaceutical, and other industries. Simulink is a block diagram environment for simulation and Model-Based Design of multidomain and embedded engineering systems. MATLAB, the language of engineers and scientists, is a programming environment for algorithm development, data analysis, visualization, and numeric computation. MathWorks is the leading developer of mathematical computing software. “Learning how to quickly and easily apply the power of NVIDIA GPUs to accelerate neural network training streamlines the process of application development and allows for more rapid deployment and faster time to market.” About MathWorks “There’s been a surge of interest in the Deep Learning with MATLAB course using NVIDIA GPUs,” said Will Ramey, senior director and global head of developer programs at NVIDIA. “This course offers a practical approach to deep learning that will help NVIDIA users to iterate quickly and converge on a solution that meets product and time-to-market requirements.” “The NVIDIA Deep Learning Institute plays a crucial role in developing hands-on training and showcasing how to use new techniques like deep learning to solve complex problems,” said David Rich, director, MATLAB marketing, MathWorks. In addition, a MATLAB container from NVIDIA GPU Cloud ( NGC), a hub for GPU-optimized AI and HPC software, provides a complete deep learning workflow that uses NVIDIA GPUs to accelerate neural network training to scale up performance across nodes. GPU Coder generates optimized CUDA code from MATLAB code for deep learning, embedded vision, and autonomous systems, which allows developers to build solutions that run efficiently on NVIDIA GPUs. MathWorks provides a comprehensive platform for building AI-driven systems that is based on decades of supporting complex engineering projects. For dates and locations, visit the Deep Learning with MATLAB course schedule. On completion, engineers, scientists, and researchers will be ready to apply GPU-accelerated deep learning techniques in MATLAB to common applications such as image classification, autonomous systems, voice recognition, and object detection. The two-day course is being offered in both instructor-led online and self-paced on-demand formats throughout the rest of 2020. MathWorks today announced that a comprehensive “Deep Learning with MATLAB” course is now available, developed in collaboration with NVIDIA’s Deep Learning Institute.
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