[51 microcontroller] [automatic download] [type-c]

Introduction: 51 microcontroller core board, type-c, automatic download

Schematic PCB

Haochen:: Desktop sound card, headphone amplifier, power amplifier, three-in-one V1.0

Introduction: "Power Amplifier and Headphone Amplifier Mini 2-in-1 V2.0" derived from 47415Y, thank you for the open source.

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PB-03Kit

Introduction: The smallest development board designed using pb03 module

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ODRIVE3.5(DRV8303)

Introduction: Big launch! Homemade odrive3.5V, 24V/30A!

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STM32 balancing car

Introduction: STM32 balancing car

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4-40pin LCD MCU universal test board V2.1

Introduction: A minimal system containing 2 types of 51 chips, which is convenient for quickly testing common circuits of various small LCD screens.

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Breathing Light-Starlight

Introduction: Third Prize in the 2022 Guangzhou City Polytechnic School of Electrical Engineering Electrical and Electronic Breathing Lamp Design Competition

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(Verified) Adjustable PD deception made by CH224K-master control STC8G1K08

Introduction: Using STC8G1K08 in sop8 package to control CH224K fast charging and receiving chip (PD deception)

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STC51-NUCLEO

Introduction: STC51-NUCLEO

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Open Source-STC15W408AS Minimal System Board

Introduction: STC15W408AS Minimal System Board

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Mini_Piano

Introduction: A simple electronic keyboard made using touch chip RH6015C and STC microcontroller, which directly touches the PCB board to produce sound.

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BTT SKR MINI E3 V2.0 3D printed motherboard

Introduction: BTT SKR MINI E3 V2.0 3D printed motherboard

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16x64 dot matrix

Introduction: 16*64 dot matrix

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Dormitory access control-RC522

Introduction: Using stm32 master control, adding a low-power Bluetooth module and a fingerprint sensor, you can use a card, fingerprint or wireless to open the dormitory door

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STC8H1K28-36I-LOFP32 minimum system

Introduction: This is my first drawing board, using automatic routing. It has been tested and can be used.

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2021 Electronic Competition F Question Country 2

Introduction: The design uses grayscale morphology to preprocess the acquired images, and combines it with a convolutional neural network constructed based on Keras to achieve rapid recognition of ward numbers in 163ms, with an accuracy of up to 95%;

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STM32f103_BLDC driver

Introduction: Three-phase brushless motor driver hardware testing

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HIP4082 4-way motor driver

Introduction: HIP40824 motor driver

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tomato_clk

Introduction: A little Pomodoro

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micro gyroscope

Introduction: Car gyroscope, the program is not open source

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