Computational Physics (Lecture 18)
Neural networks explained with the example of feedforward vs. recurrent networks. Feedforward networks propagate data, while recurrent models allow loops for cascade effects. Recurrent networks are less influential but closer to the brain's function. Introduction to handwritten digit classification
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Understanding Computer Networks: Types and Characteristics
In the realm of computer networks, nodes share resources through digital telecommunications networks. These networks enable lightning-fast data exchange and boast attributes like speed, accuracy, diligence, versatility, and vast storage capabilities. Additionally, various types of networks exist tod
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Improving Multi-Link Power Management Efficiency in IEEE 802.11 Networks
The document discusses challenges with per-link power mode changes in multi-link scenarios in IEEE 802.11 networks, proposing a solution for more efficient power management. It addresses issues such as latency and inefficiencies in signaling for power mode changes, introducing scheduled multi-link p
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Enhancing R-TWT with Multi-AP Coordination in IEEE 802.11 Networks
Delve into the world of IEEE 802.11 wireless networks as this document explores solutions for multi-AP coordination for R-TWT, focusing on improving tail latency, jitter, and medium protection. Enhancements in R-TWT operation, coordination scenarios, and solutions for multi-AP deployments are discus
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Progress on IEEE 802.11 Multi-link Setup
Significant developments have been made in the multi-link setup within the IEEE 802.11 framework. The focus is on allowing only one STA in the MLD framework, differentiation with STA-level associations, and the rationale behind restricting to one STA. Proposals for defining multi-link devices and re
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Understanding Artificial Neural Networks From Scratch
Learn how to build artificial neural networks from scratch, focusing on multi-level feedforward networks like multi-level perceptrons. Discover how neural networks function, including training large networks in parallel and distributed systems, and grasp concepts such as learning non-linear function
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Understanding Back-Propagation Algorithm in Neural Networks
Artificial Neural Networks aim to mimic brain processing. Back-propagation is a key method to train these networks, optimizing weights to minimize loss. Multi-layer networks enable learning complex patterns by creating internal representations. Historical background traces the development from early
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IEEE 802.11-20/0772r2 Multi-Link Elements Overview
IEEE 802.11-20/0772r2 discusses various aspects of multi-link elements in the context of IEEE 802.11 standards. The document covers the need for efficient element ID extension, different multi-link element structures, including authentication algorithms, common controls, and sub-elements organizatio
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Understanding Multi-AP Operation in IEEE 802.11-20-0617/r3
Explore the basic definitions and key features of Multi-AP operation in the IEEE 802.11 standard. Learn about Multi-AP Candidate Set (M-AP-CS) and Multi-AP Operation Set (M-AP-OS) along with their participants and formation. Delve into the concepts of Coordinator AP, Coordinated AP(s), and reliable
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IEEE 802.11-2020 Multi-Link Reference Model Discussion
This contribution discusses the reference model to support multi-link operation in IEEE 802.11be and proposes architecture reference models to support multi-link devices. It covers aspects such as baseline architecture reference models, logical entities in different layers, Multi-Link Device (MLD) f
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Understanding Interconnection Networks in Multiprocessor Systems
Interconnection networks are essential in multiprocessor systems, linking processing elements, memory modules, and I/O units. They enable data exchange between processors and memory units, determining system performance. Fully connected interconnection networks offer high reliability but require ext
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IEEE 802.11-23/1980r1 Coordinated AP-assisted Medium Synchronization Recovery
This document from December 2023 discusses medium synchronization recovery leveraging multi-AP coordination for multi-link devices. It covers features such as Multi-link device (MLD), Multi-link operation (MLO), and Ultra High Reliability (UHR) capability defined in P802.11bn for improvements in rat
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Understanding Multi-Band Multi-Channel Concept in IEEE 802.11be
Exploring the benefits of Multi-Band Multi-Channel (MBMC) operation in IEEE 802.11be, this study delves into the efficient use of spectrum, increased data rates, and network load balancing. It also discusses the envisioned usage models and compares Single Band Operation with Multi-Band Operation, hi
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Introduction to Neural Networks in IBM SPSS Modeler 14.2
This presentation provides an introduction to neural networks in IBM SPSS Modeler 14.2. It covers the concepts of directed data mining using neural networks, the structure of neural networks, terms associated with neural networks, and the process of inputs and outputs in neural network models. The d
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Enhancing IEEE 802.11 with Multi-Link Acknowledgment Mechanism
This document explores the concept of multi-link transmission in IEEE 802.11 networks as a means to enhance peak throughput. It delves into the proposal of a multi-link block acknowledgment mechanism for more efficient data transmission. The discussion includes details on existing block acknowledgme
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IEEE 802.11-20/0370r0 Multi-link Power Save Discussion
The document discusses multi-link power saving in the IEEE 802.11be standard. It reviews extreme low power multi-link operation modes, emphasizing the importance of enabling a single link for practical power savings. The proposed extreme low power mode introduces fixed and dynamic anchor links for e
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IEEE 802.11-19/1358r5 Multi-Link Operation Management Overview
This document provides insights into the multi-link operation management proposed for IEEE 802.11-19/1358r5 standard by MediaTek Inc. The concept involves handling multi-link entities, such as APs and STAs, for improved performance in different environments. It discusses the architecture, motivation
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Multi-band Discovery Assistance for IEEE 802.11ay Networks
This document discusses the implementation of multi-band discovery assistance for IEEE 802.11ay networks to improve robustness and reduce latency in consumer devices. It focuses on reducing overhead latency, enabling TDD channel access, and utilizing multi-band signaling for various network operatio
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IEEE 802.11-20/0136r2: Virtual Carrier Sense in Multi-Link Networks
In this document presented in February 2020, the focus is on the implementation of virtual carrier sense (CS) in the context of multiple links in IEEE 802.11-20/0136r2. The advantages of NAC in asynchronous multi-link scenarios are discussed, emphasizing the mitigation of the hidden node problem and
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Enhancing Throughput in Multi-Hop Wireless Networks Using Reconfigurable Antennas
In this study presented at IEEE SECON 2018, the authors investigate the throughput limits of multi-hop wireless networks employing reconfigurable antennas (RAs). Challenges such as unreliable links, interference, and large overhead are addressed, with existing approaches at both the link/network lay
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P-Rank: A Comprehensive Structural Similarity Measure over Information Networks
Analyzing the concept of structural similarity within Information Networks (INs), the study introduces P-Rank as a more advanced alternative to SimRank. By addressing the limitations of SimRank and offering a more efficient computational approach, P-Rank aims to provide a comprehensive measure of si
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Virtual Carrier Sense in Asynchronous Multi-Link Networks
Exploring the implementation of virtual carrier sense in asynchronous multi-link networks based on IEEE 802.11 standards. The presentation discusses the benefits of using NAV (Network Allocation Vector) in asynchronous multi-link setups to avoid hidden node issues, improve throughput, and latency. I
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Virtual Carrier Sense in Multi-Link Networks
This document discusses the implementation and advantages of virtual carrier sense in multi-link networks under the IEEE 802.11 standard. It explores the operation of multi-link setups, asynchronous communication benefits, and the necessity of multiple contention channels. The concept of NAV (Networ
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Understanding Advanced Classifiers and Neural Networks
This content explores the concept of advanced classifiers like Neural Networks which compose complex relationships through combining perceptrons. It delves into the workings of the classic perceptron and how modern neural networks use more complex decision functions. The visuals provided offer a cle
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Performance Aspects of Multi-link Operations in IEEE 802.11-19/1291r0
This document explores the performance aspects, benefits, and assumptions of multi-link operations in IEEE 802.11-19/1291r0. It discusses the motivation for multi-link operation in new wireless devices, potential throughput gains, classification of multi-link capabilities, and operation modes. The s
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Performance Aspects of Multi-link Operations in IEEE 802.11-19/1291r3
This document discusses the motivation, assumptions, and classifications related to multi-link operations in IEEE 802.11-19/1291r3 standard. It explores the benefits of multi-link capabilities in new wireless devices, such as improved throughput, reduced latency, and potential for link aggregation.
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Multi-Stage, Multi-Resolution Beamforming Training for IEEE 802.11ay
In September 2016, a proposal was introduced to enhance the beamforming training procedures in IEEE 802.11ay for increased efficiency and MIMO support. The proposal suggests a multi-stage, multi-resolution beamforming training framework to improve efficiency in scenarios with high-resolution beams a
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Understanding Overlay Networks and Distributed Hash Tables
Overlay networks are logical networks built on top of lower-layer networks, allowing for efficient data lookup and reliable communication. They come in unstructured and structured forms, with examples like Gnutella and BitTorrent. Distributed Hash Tables (DHTs) are used in real-world applications li
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Understanding Networks: An Introduction to the World of Connections
Networks define the structure of interactions between agents, portraying relationships as ties or links. Various examples such as the 9/11 terrorists network, international trade network, biological networks, and historical marriage alliances in Florence illustrate the power dynamics within differen
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Understanding Network Analysis: Whole Networks vs. Ego Networks
Explore the differences between Whole Networks and Ego Networks in social network analysis. Whole Networks provide comprehensive information about all nodes and links, enabling the computation of network-level statistics. On the other hand, Ego Networks focus on a sample of nodes, limiting the abili
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Proposal for Common Multi-link Element in IEEE 802.11-20/0772r0
Various multi-link elements have been proposed in IEEE 802.11 standards, leading to potential space limitations. The proposal suggests a common multi-link element with a Type field to distinguish different usages efficiently, potentially streamlining multi-link operations without unnecessary complex
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Multi-AP Coordination for Low Latency Traffic Transmission
The document discusses the integration of multi-access point (AP) coordination to enhance the transmission of low-latency traffic in wireless networks. It addresses the challenges and introduces modes of operation capable of reducing latency and improving reliability for low-latency (LL) traffic tra
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Evolution of Networking: Embracing Software-Defined Networks
Embrace the future of networking by transitioning to Software-Defined Networks (SDN), overcoming drawbacks of current paradigms. Explore SDN's motivation, OpenFlow API, challenges, and use-cases. Compare the complexities of today's distributed, error-prone networks with the simplicity and efficiency
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IEEE 802.11-19/0773r0 Multi-link Operation Framework Summary
The document discusses the multi-link operation framework for IEEE 802.11-19/0773r0, focusing on load balancing and aggregation use cases. It introduces terminology related to multi-link logical entities and provides examples of multi-link AP and non-AP logical entities. The framework considers stee
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Understanding Multi-morbidity and Deprivation in UK General Practice
Exploring the association between multi-morbidity, deprivation, and life expectancy in the context of UK general practice. The research aims to quantify socio-economic inequalities in chronic disease onset and life expectancy, particularly among older populations with multi-morbidity. Methods includ
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IEEE 802.11-17: Enhancing Multi-Link Operation for Higher Throughput
The document discusses IEEE 802.11-17/xxxxr0 focusing on multi-link operation for achieving higher throughput. It covers motions adopted in the SFD related to asynchronous multi-link channel access, mechanisms for multi-link operation, and shared sequence number space. Additionally, it explores the
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Revisiting DMG Multi-Band Discovery Assistance for 802.11ay Networks
Presentation by Kazuyuki Sakoda from Sony proposing the extension of DMG multi-band discovery assistance in 802.11ay networks to improve neighbor device discovery beyond AP coverage. The focus is on enhancing network efficiency, low-latency communication, and robustness for VR applications in high-f
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Overview of DICOM WG21 Multi-Energy Imaging Supplement
The DICOM WG21 Multi-Energy Imaging Supplement aims to address the challenges and opportunities in multi-energy imaging technologies, providing a comprehensive overview of imaging techniques, use cases, objectives, and potential clinical applications. The supplement discusses the definition of multi
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Understanding Interconnection Networks in Embedded Computer Architecture
Explore the intricacies of interconnection networks in embedded computer architecture, covering topics such as connecting multiple processors, topologies, routing, deadlock, switching, and performance considerations. Learn about parallel computer systems, cache interconnections, network-on-chip, sha
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Understanding Deep Generative Bayesian Networks in Machine Learning
Exploring the differences between Neural Networks and Bayesian Neural Networks, the advantages of the latter including robustness and adaptation capabilities, the Bayesian theory behind these networks, and insights into the comparison with regular neural network theory. Dive into the complexities, u
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