Liquid Instruments’ Post

#Engineers: Join us at the #IMS2024 workshop to learn a convolutional neural network (CNN) for channel estimation using OTA measurements through mmWave PAAM and AMD RFSoC-based 5G NR receiver in a CATR chamber. https://spr.ly/60455IqLx

#Engineers: Join us at the #IMS2024 workshop to learn a convolutional neural network (CNN) for channel estimation using OTA measurements through mmWave PAAM and AMD RFSoC-based 5G NR receiver in a CATR chamber. https://spr.ly/60495BGKB

Transformer Neural Networks (TNNs) are helping Motional’s onboard perception system predict future object movements and plan a safe course forward. Learn more about how Motional is pushing the boundaries of AV technology for a smoother, safer ride. https://lnkd.in/ee9f56AX

I am pleased to present a certificate for a paper that has been accepted by the MDPI Energies journal. The title of the paper is "Intelligent Integration of Vehicle-to-Grid (V2G) and Vehicle-for-Grid (V4G) Systems: Leveraging Artificial Neural Networks (ANN) for Smart Grid."

Neural network-based fault detection, location and classification in microgrid Uses neural networks to identify, locate, and classify faults in microgrids. https://lnkd.in/gFas9m5k https://lnkd.in/gf7mDhjs #NeuralNetwork #FaultDetection #Microgrid #SmartGrid #RenewableEnergy #AIinEnergy #GridReliability #EnergyInnovation #FaultClassification #ElectricPower #TechInEnergy #SustainableTech #SmartEnergy #MachineLearning #PowerSystems

Spiking Neural Network for LPI Radar Classification: the principle is very interesting, the time frequency image of the radar signal (LFM, Costas, ...) is converted into sipke trains, using LIF neurons according to code rate, this spiking structure interfaces with convolutional layers, max pooling layers and fully connected layers (just like DNN) to give out scores for the different classes (modulation types of the radar signals). It is interesting to note how a continuous time representation, output of the spiking network, interfaces with the features maps of the convolutional layers....

Neural operators map multiple functions to different functions, possibly in different spaces, unlike standard neural networks. Hence, neural operators allow the solution of parametric ordinary differential equations (ODEs) and partial differential equations (PDEs) for a distribution of boundary or initial conditions and excitations, but can also be used for system identification as well as designing various components of digital twins. #HPC #neuralnetwork #artificialintelligence #neuraloperator #differentialequation https://lnkd.in/d25EiDUP

Neural networks detect and classify faults in power systems accurately. Purchase link for Indian customers: https://lnkd.in/gvP32Y_c Purchase link for other than Indian customers: https://lnkd.in/g6Ye_HxM https://lnkd.in/gYA6wW-a #NeuralNetwork #PowerSystem #FaultDetection #FaultClassification #SmartGrid #EnergyManagement #PowerEngineering #ArtificialIntelligence #MachineLearning #ElectricalSafety #GridReliability #SystemProtection #AdvancedTechnology #FaultAnalysis #IntelligentSystems

Once a year, the IEEE Signal Processing Society lists its 25 most downloaded articles and magazine papers. This year I am honored to have 4 different papers in this list. These papers are: 1. "Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing", with Sundeep Prabhakar Chepuri, Fan Liu, George Alexandropoulos, Stefano Buzzi, and Yonina Eldar 2. "Multiuser MIMO Wideband Joint Communications and Sensing System With Subcarrier Allocation", with Nhan Nguyen, Yonina Eldar, and Markku Juntti 3. "KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics" (second year in a row), with Guy Revach, Ph.D. Candidate, Xiaoyong Ni, Adrià López Escoriza, Ruud van Sloun, and Yonina Eldar 4. Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar" (third year in a row), with Xiang Liu, Tianyao Huang, Liu Yimin, Jie Zhou, and Yonina Eldar

Heard about Neural Quantum Processor Ultra? Enjoy a powerful and cinematic experience. Combining 20 multilayer neural networks, the AI-powered processor intelligently analyzes images to recreate every detail in every pixel. Automatic brightness adjustment, contrast enhancement and other improvements will perfect the resolution of the content. LV: bit.ly/3yHWFzE EE: bit.ly/4bFvSCy LT: bit.ly/456C1VT