Proponent
发表于 2025-3-30 11:21:07
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chisel
发表于 2025-3-30 15:26:29
OLED Using DMA,(direct memory access) Organic light-emitting diode (OLED) controller, which can be exploited to perform the I/O operations and leave more cycles available for the CPU. This chapter will explore how to set up and use that DMA controller to drive the OLED device.
reperfusion
发表于 2025-3-30 20:06:00
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Scintillations
发表于 2025-3-30 21:35:26
leading to advanced multi-tasking applications.Features libo.Using FreeRTOS and libopencm3 instead of the Arduino software environment, this book will help you develop multi-tasking applications that go beyond Arduino norms. In addition to the usual peripherals found in the typical Arduino device, t
Hyperalgesia
发表于 2025-3-31 02:15:24
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是他笨
发表于 2025-3-31 05:17:32
CAN Bus, Bosch released the developed CAN protocol at the SAE Congress (Society of Automotive Engineers).. In 1991 the CAN 2.0 protocol was published by Bosch and was adopted in 1993 as the international standard (ISO 11898). Since then, automobiles have used the protocol for communication and to reduce wiring harness sizes by use of the bus.
iodides
发表于 2025-3-31 10:07:36
Book 20181st editionArduino norms. In addition to the usual peripherals found in the typical Arduino device, the STM32 device includes a USB controller, RTC (Real Time Clock), DMA (Direct Memory Access controller), CAN bus and more. .Each chapter contains clear explanations of the STM32 hardware capabilities to help ge
果核
发表于 2025-3-31 16:21:53
scheidung und den daraus resultierenden Konsequenzen für die involvierten Unternehmen — interpretiert eben vornehmlich als Erfolgswirkungen — verdeutlicht und insofern der aus ökonomischer Perspektive geforderten ganzheitlichen (strategisch orientierten) Betrachtung des Sachverhalts am nächsten komm
Trigger-Point
发表于 2025-3-31 21:22:55
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摄取
发表于 2025-4-1 00:20:20
Jayanti Nayak,Therese Keane,Kurt Seemannes. The developed method used three deep convolutional neural networks named DCNN1, DCNN2, and DCNN3, three deep convolutional neural networks combined with deep recurrent neural networks named DCNN-RNN1, DCNN-RNN2, and DCNN-RNN3, and two autoencoder neural networks named AE1 and AE2, to maximize th