Aaditya Pandey’s Post

FYI Linear phase is a property of a filter where the phase response of the filter is a linear function of frequency. The result is that all frequency components of the input signal are shifted in time (usually delayed) by the same constant amount (the slope of the linear function), which is referred to as the group delay. Consequently, there is no phase distortion due to the time delay of frequencies relative to one another. #phase #audio #sound #teamadamson #acoustics #education #learning

𝗔𝗱𝗮𝗺𝘀𝗼𝗻 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝘀 𝗟𝗮𝗸𝗲 𝗟𝗶𝗯𝗿𝗮𝗿𝘆 𝗩𝟲.𝟬 Adamson Systems Engineering has launched Lake Library V6.0, delivering improvements designed to elevate system performance and simplify user workflow. This latest release introduces unified phase matching across products, ensuring seamless integration and compatibility, alongside a range of other significant updates. Key highlights include: • 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗟𝗶𝗻𝗲𝗮𝗿 𝗣𝗵𝗮𝘀𝗲 𝗣𝗿𝗲𝘀𝗲𝘁𝘀: All existing linear phase presets have been meticulously revised. • 𝗡𝗲𝘄 𝗟𝗶𝗻𝗲𝗮𝗿 𝗣𝗵𝗮𝘀𝗲 𝗣𝗿𝗲𝘀𝗲𝘁𝘀 for all passive S-Series and IS-Series point sources. • 𝗜𝗦𝟳𝗰 𝗣𝗿𝗲𝘀𝗲𝘁𝘀 • 𝗥𝗲𝘃𝗶𝘀𝗲𝗱 𝗟𝗶𝗺𝗶𝘁𝗲𝗿 in all NH4 high frequency presets for better performance. Mario Ahrberg, Adamson’s Head of Applications EMEA: “By utilizing the new Lake XP modules, we unlocked a vast array of features. With this update, we’re proud to deliver the results of years of research. I’m confident our users will appreciate the new presets and the streamlined workflow.” Additional updates include: • Optimized 60 Hz Subwoofer Presets: Specifically designed for use in combination with VGt, E15, and E12, enhancing low-end performance. • Streamlined User Experience: A new folder structure and Amplification Chart make it easier than ever to access and apply presets. For a comprehensive list of updates, refer to the 𝗥𝗲𝗹𝗲𝗮𝘀𝗲 𝗡𝗼𝘁𝗲𝘀. The Adamson Lake Library V6.0 is available for download on adamson.ai: https://lnkd.in/egY-XnWq It is also included in the latest 𝗟𝗮𝗸𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹𝗹𝗲𝗿 𝟴.𝟭.𝟰 software. #proaudio #lakecontroller #TeamAdamson

In this article, the authors focus on a generic #multiterminal (#remote) #source #coding #scenario in which, via a joint design, several intermediate nodes must locally compress their noisy observations from various sets of user / source signals ahead of forwarding them through multiple error-free and rate-limited channels to a (remote) processing unit. Although different local compressors might receive noisy observations from a / several common source signal(s), each local quantizer should also compress noisy observations from its own, i.e., uncommon source signal(s). This, in turn, yields a highly generalized scheme with most flexibility w.r.t. the assignment of users to the serving nodes, compared to the State-of-the-Art techniques designed exclusively for a common source signal. Following the #Information #Bottleneck (#IB) philosophy, we choose the Mutual Information as the fidelity criterion here, and, by taking advantage of the Variational Calculus, they characterize the form of stationary solutions for two different types of processing flow/ strategy. They utilize the derived solutions as the core of our devised algorithmic approach, the #GE #neralized #M #ultivariate #IB (#GEMIB), to (efficiently) address the corresponding design problems. They further provide the respective convergence proofs of GEMIB to a stationary point of the pertinent objective functionals and substantiate its effectiveness by means of numerical investigations over a couple of (typical) digital transmission scenarios. ---- Shayan Hassanpour, Alireza Danaee, Dirk Wübben, Armin Dekorsy More details can be found at this link: https://lnkd.in/erBRh6fF

Join us October 16th for From Chaos to Clarity: Conceptual Modeling for Complex Systems https://lnkd.in/eNw6tSQ2 In this webcast, Wolfgang Maass, Hyoil Han, and Hasan Yasar discuss key principles of conceptual modeling and explore its significance in various domains and its role in driving successful system design. #systemdesign #conceptualmodeling #ER2024 #complexsystems

[COMST Survey] A Survey on Resource Management in Joint Communication and Computing-Embedded SAGIN   The advent of the 6G era aims for ubiquitous connectivity, with the integration of non-terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As manufacturing advances and user demands evolve, space-air-ground integrated networks (SAGIN) with computational capabilities emerge as viable solutions for services requiring low latency and high computational power. Resource management within joint communication and computing-embedded SAGIN (JCC-SAGIN) presents greater complexity than traditional terrestrial networks. This complexity arises from the spatiotemporal dynamics of network topology and service demand, the interdependency of large-scale resource variables, and intricate tradeoffs among various performance metrics. Thus, a thorough examination of resource management strategies in JCC-SAGIN is crucial, emphasizing the role of non-terrestrial platforms with processing capabilities in 6G.   In this context, the paper titled “A Survey on Resource Management in Joint Communication and Computing-Embedded SAGIN” by Qian Chen, Zheng Guo, Weixiao Meng, Shuai Han, Cheng Li, and Tony Q. S. Quek, provides a holistic review of solutions and insights for resource management in JCC-SAGIN by merging academic and industrial perspectives. This paper begins by reviewing the architecture, enabling technologies, and applications in JCC-SAGIN. Then, a detailed overview of resource management modeling and optimization methods is offered, encompassing both traditional optimization approaches and learning-based intelligent decision-making frameworks. Finally, the prospective research directions are outlined in JCC-SAGIN. Paper link: https://lnkd.in/gQ2cXjpU

🚀 𝗚𝗿𝗼𝗸𝗸𝗲𝗱 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 𝗮𝗿𝗲 𝗜𝗺𝗽𝗹𝗶𝗰𝗶𝘁 𝗥𝗲𝗮𝘀𝗼𝗻𝗲𝗿𝘀 Transformer when trained beyond the point of overfitting (𝗚𝗿𝗼𝗸𝗸𝗲𝗱), reveal a remarkable ability to implicitly reason and generalize effectively in both in-distribution (ID) and out-of-distribution (OOD) scenarios, particularly for comparison tasks. 🔍One notable point behind this article is that the authors begin to propose different reasoning tasks such as composition and comparison, marking a significant step towards understanding which reasoning abilities work well and which need further refinement from the transformer architecture perspective. 👉Authors, still encounter challenges with compositional reasoning tasks. To address this, the authors suggest enhancing the model with a cross-layer memory-sharing mechanism. 👉A notable comparison between parametric memory for complex reasoning and non-parametric approaches (such as prompting, direct or CoT ones) highlights the superiority of parametric memory in complex reasoning as authors proposed. https://lnkd.in/ep5N-FpR https://lnkd.in/ez3ANVnX #artificialIntelligence #data #llms #reasoning

Important concept for #dataengineers as it has been asked many times in the interviews and you should have good understanding of the same. The CAP theorem, also known as Brewer's theorem, is a computer science concept that explains how a distributed system can only guarantee two out of three properties: Consistency Every read receives the most recent write or an error. Availability Every request received by a non-failing node in the system must result in a response. Partition tolerance The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes. If you want to understand it more practically, please have a look below: https://lnkd.in/gGjUTMVR #dataengineering #captheorem #systemdesign #interviewquestions

Think traditional grids are the best for service matching? Think again! 🚀 Our latest #blog dives into how the #HexagonalHierarchicalSpatialIndex transforms real-time service matching by making it #faster, more #accurate, and #scalable. Using efficient hexagonal grids, this innovative approach cuts down wait times and ensures the nearest provider is just a tap away. Whether you're looking at high-demand scenarios or low-density regions, this method optimizes every search. Check it out here: [https://lnkd.in/ggZ_DdRT] Written by Tanishq Agarwal, Backend Software Engineer #SpatialIndexing #ServiceMatching #HexagonalGrid #TechInnovation #BackendEngineering #ScalableTech #EfficientMatching #RealTime #webknot

A "few" years ago I wrote this paper showing how you can leverage concepts of multi-grid computing to construct hierarchical control architectures. This was a short paper (5 pages) but I learned a lot by writing this, as it helped me reconcile/connect ideas from optimal control, optimization, and multi-grid computing. It took me nearly 3 years to figure out how to do this. One thing that I learned from writing this paper is that, when you adventure into research areas that are not yours, you often find similar concepts, approaches, and ways of thinking (developed by communities independently when trying to solve different problems). This reveals that there are "universal" approaches to solving problems. For instance, multi-grid is a general paradigm to deal with complexity and it is used by diverse communities to deal with multi-scale problems. Hierarchical control is fundamentally trying to do the same... try to mitigate disturbances and behavior arising at different scales. People doing molecular simulations also apply this to capture phenomena emerging at different scales. Industrial/societal organizations are also naturally organized hierarchically to deal with complexity. If you want to learn more about this topic, check: https://lnkd.in/gNDWxqTP #control #optimization #computing #multiscale #phdresearch

Learn how you can get sophisticated segmentation without changes to your network architecture or application downtime. #AkamaiSecurity