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• Approximate Matrix Multiplication based Hardware Accelerator to achieve the next 10x in Energy Efficiency: Training Strategy And Algorithmic optimizations
  * 30% Algorithmic optimizations
  6 KB (823 words) - 16:32, 3 November 2022

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• Power Saver Mode for Cellular Internet of Things Receivers
  ...t, methods to save power for 2G EC-GSM-IoT shall be studies. In particular algorithmic approaches to early detect high decoding success probability before all bli
  2 KB (277 words) - 17:59, 29 March 2017
• Advanced 5G Repetition Combining
  ...t step in your project, you will study ways to reduce the complexity on an algorithmic level. Based on this, you will come up with an efficient architecture to im
  3 KB (345 words) - 10:52, 5 April 2022
• Towards Online Training of CNNs: Hebbian-Based Deep Learning
  ...ollers – in many cases using convolutional neural networks (CNNs) as the algorithmic “tool” to extract semantic information out of raw data streams. Doing t
  6 KB (909 words) - 19:50, 30 May 2017
• Sub Noise Floor Channel Estimation for the Cellular Internet of Things
  ...n option. This project is a perfect opportunity to solve a clearly defined algorithmic problem and actually test the result in a complete system with real world d
  2 KB (295 words) - 11:27, 6 November 2017
• Deep Learning Projects
  * '''Algorithmic''' - you will mainly make algorithmic evaluations using languages and frameworks like e.g. Python, Pytorch, Tenso
  18 KB (2,473 words) - 19:29, 19 February 2024
• Make Cellular Internet of Things Receivers Smart
  ...alog front-end. This project is a perfect opportunity to solve a hot topic algorithmic problem and make cellular IoT receivers smart.
  2 KB (289 words) - 18:00, 29 March 2017
• Deep-Learning Based Phoneme Recognition from a Ultra-Low Power Spiking Cochlea
  ...ollers – in many cases using convolutional neural networks (CNNs) as the algorithmic “tool” to extract semantic information out of raw data streams. Doing t
  6 KB (920 words) - 16:33, 3 October 2019
• Tiny CNNs for Ultra-Efficient Object Detection on PULP
  ...ollers – in many cases using convolutional neural networks (CNNs) as the algorithmic “tool” to extract semantic information out of raw data streams. Doing t
  5 KB (794 words) - 13:19, 13 January 2017
• Satellite Internet of Things
  ...ottlenecks. These shall be eliminated in the second part of the project by algorithmic optimizations and/or changes to the physical-layer specification itself.
  3 KB (393 words) - 13:53, 13 November 2020
• Interference Cancellation for the cellular Internet of Things
  ...erference suppression requirements defined by 3GPP [1]. The most promising algorithmic candidate will be implemented in hardware, either in VHDL or with an HLS ap
  2 KB (269 words) - 13:15, 31 October 2019
• Hyperdimensional Computing
  * '''Algorithmic''' design and optimizations (Matlab/ Python) ...f efficient techniques in analog front-end, digital signal processing, and algorithmic aspects. The abilities of HD computing for one-shot, online learning, and i
  10 KB (1,341 words) - 10:46, 25 April 2018
• Human Intranet
  Overall, our projects cover '''algorithmic, hardware/software, and system level''' design and developments.
  17 KB (2,419 words) - 20:09, 10 March 2024
• Positioning for the cellular Internet of Things
  A pure implementation project or combined with algorithmic approaches is possible depending on the interest of the student(s).
  1 KB (204 words) - 13:14, 31 October 2019
• IBM Research
  ...search (listed in below table) awaiting in this direction spans high-level algorithmic exploration all the way to efficient hardware design for emerging computati ...e-change memory chips comprising more than 1 million devices to high-level algorithmic development in a deep learning framework such as TensorFlow or PyTorch. It
  9 KB (1,330 words) - 15:20, 15 March 2024
• Phase-change memory devices for emerging computing paradigms
  ...ious aspects of the project such as device fabrication, circuit design and algorithmic development ...there are several challenges that need to be overcome at both hardware and algorithmic = levels to realize reliable and accurate inference engines based on comput
  5 KB (640 words) - 14:13, 23 June 2021
• Accurate deep learning inference using computational memory
  ...there are several challenges that need to be overcome at both hardware and algorithmic levels to realize reliable and accurate inference engines based on computat ...e-change memory chips comprising more than 1 million devices to high-level algorithmic development in a deep learning framework such as TensorFlow or PyTorch. It
  5 KB (628 words) - 12:51, 17 April 2020
• Knowledge Distillation for Embedded Machine Learning
  [[Category:Algorithmic]]
  5 KB (670 words) - 15:14, 4 August 2022
• Efficient TNN compression
  [[Category:Algorithmic]]
  3 KB (438 words) - 08:41, 17 February 2021
• Biomedical Circuits, Systems, and Applications
  ...ongoing around the human body, from chip design, to system development, to algorithmic investigations in various application scenarios. In the following sections
  9 KB (1,292 words) - 19:16, 23 March 2024
• Exploring schedules for incremental and annealing quantization algorithms
  [[Category:Algorithmic]]
  6 KB (868 words) - 14:15, 15 February 2024

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