Search Results for "mimo"
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Showing 16 open source projects for "mimo"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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MiMo Code
Where Models and Agents Co-Evolve
MiMo-Code is a terminal-native AI coding assistant built for real software projects. It can read and edit code, run commands, manage Git, and preserve project knowledge across sessions. The tool includes multiple agent modes, including a build mode for development, a plan mode for read-only analysis, and a compose mode for structured workflows. -
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MiMo-V2.5-ASR
Robust Speech Recognition Across Languages, Dialects
MiMo-V2.5-ASR is an advanced automatic speech recognition system developed as part of Xiaomi’s MiMo AI ecosystem. It is designed to handle complex acoustic environments, including noisy conditions and diverse speaker variations. The model supports multiple languages and dialects, enabling robust transcription across global use cases. It leverages modern deep learning architectures to improve accuracy and adaptability in real-world scenarios. -
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MiMo-V2-Flash
MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation
...The repository typically serves as a launch point for running the model, understanding its intended use cases, and reproducing or extending its evaluation on reasoning and agent-style tasks. In short, MiMo-V2-Flash targets the “high-speed, high-competence” lane for modern LLM applications. -
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Kun
AI agent workspace with Code and Write modes built into your apps
...The application includes a Code workspace for real repositories and a Write workspace for Markdown writing, editing, previewing, and exporting. It uses DeepSeek, Xiaomi MiMo, and MiniMax as its default model combination while still allowing custom providers. Kun includes a local runtime through kun serve, local session storage, tool approvals, permission modes, inline diffs, and change review panels. It is useful for users who want an AI coding environment that treats planning, documentation, implementation, and acceptance review as one continuous workflow. -
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ProxSDP.jl
Semidefinite programming optimization solver
ProxSDP is an open-source semidefinite programming (SDP) solver based on the paper "Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting". The main advantage of ProxSDP over other state-of-the-art solvers is the ability to exploit the low-rank structure inherent to several SDP problems. -
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Fuzzy Logic Tools (FLT) is a C++ framework for storage, analysis and design of fully general multiple-input multiple-output (MIMO) Takagi-Sugeno fuzzy control systems, without constraints in the order of either the inputs or the output vectors.
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MIMO OFDM
MATLAB implementation source code accompanying the book MIMO-OFDM
This repository contains the MATLAB implementation source code accompanying the book “MIMO-OFDM 无线通信技术及 MATLAB 实现” (MIMO-OFDM Wireless Communication Technology and MATLAB Implementation). The repository is structured to match chapters in the book, providing code for topics such as OFDM basics, MIMO channel models, channel estimation, PAPR, spatial multiplexing, diversity techniques, etc. It helps readers replicate examples in the textbook and test MATLAB simulations of wireless communication schemes. ... -
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nexmon
The C-based Firmware Patching Framework for Broadcom/Cypress WiFi Chip
...It allows using non-standard channels such as 80 MHz bandwidth in the 2.4 GHz bands. It allows to set of arbitrary transmission powers. It allows patching the D11 core's real-time MAC implementation. It allows to extract of CSI of up to 4x4 MIMO transmissions at 80 MHz bandwidth. -
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Enhanced 3D ITU channel Model
A complete 3D stochastic channel model for urban and rural environment
This enhanced version of the existing 2D ITU channel model provides elevation related statistics in addition to the azimuth plane. The modified LSPs statistics are based on 3D ray tracer tool ( Smart Internet lab-Bristol University) and covers range of frequency (600 MHz, 2400 MHz and 5900 MHz) bands and environments (urban and rural). A user interface file is provided for easy setup of channel related parameters. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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pi+Arch+Squeezelite+Jivelite
Jivelite + Squeezelite running on a Raspberry Pi and USB Touchscreen
This is an image of Arch Linux on a Raspberry Pi configured with Jivelite and Squeezelite, and configured to use a USB Displaylink Touchscreen (either Mimo or Lilliput). User is "squeezeuser" with a password of "squeeze". Root user password is "root". -
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MIMO
SMS Marketing
MIMO is a online service that allow send SMS Marketing -
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...Our research group (DEI - University of Padova) mainly focuses on MAC layer (HARQ - allocation - scheduling), mobility, traffic modelization, creation of multimedia applications, MIMO.
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MiMo-V2.5
Omnimodal AI model for agents, coding, and long-context tasks
MiMo-V2.5 is a native omnimodal large language model developed by Xiaomi, designed for advanced agentic workflows, multimodal reasoning, and long-context processing. Built on a Mixture-of-Experts architecture with approximately 309B total parameters and around 15B activated per inference, it balances high capability with efficient execution. -
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MiMo-V2.6-Flash
Efficient 309B omnimodal MoE for coding, agents, vision, and audio
MiMo-V2.6-Flash is Xiaomi MiMo’s efficiency-balanced open-weight omnimodal model, designed to scale reinforcement learning across coding, general agents, visual tasks, and cybersecurity. Its sparse Mixture-of-Experts architecture contains 309B total parameters while activating only 15B per token, using 256 routed experts with eight active per token. -
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MiMo-V2.6-Pro
1T omnimodal MoE model for coding, agents, and long-horizon reasoning
MiMo-V2.6-Pro is Xiaomi MiMo’s flagship open-weight omnimodal model, built to scale reinforcement learning toward self-improvement across coding, agents, vision, and cybersecurity. Its sparse Mixture-of-Experts architecture contains 1.02T total parameters with 42B activated per token, using 384 routed experts with eight active per token. -
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MiMo-V2.5-Pro
Flagship MoE model for long-context agents and complex coding
MiMo-V2.5-Pro is Xiaomi’s flagship Mixture-of-Experts (MoE) model built for the most demanding agentic, software engineering, and long-horizon reasoning tasks. It features approximately 1.02 trillion total parameters with 42B activated per inference, balancing extreme capability with efficient execution. The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. ...
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