Nuvoton Technology Corporation

Tzu-Lan Shen

Chih-Ping Lu

Nai-Wen Cheng

Yu-Che Hsieh

Woan-Shiuan Chien

Cheng-Hui Chen

Pin-Ren Chen

Yu-Ti Hao

Chih-Yuan Wu

A control chip coupled to a central processing unit (CPU) and including a selection circuit, a buffer circuit, a calculation circuit, and a motion judgment circuit is provided. The selection circuit selects some of the first image macro-blocks of a first image frame and some of the second image macro-blocks of a second image frame. The buffer circuit stores the selected first and second image macro-blocks. The calculation circuit accesses the buffer circuit and calculates the differences between the selected first and second image macro-blocks to generate a calculated result. The motion judgment circuit determines whether the first and second image frames are the same according to the calculated result. In response to the second image frame not being the same as the first image frame, the motion judgment circuit wakes up the CPU so that the CPU enters a normal mode from a low-power mode.

Control chip and dynamic image judgment method

A method for updating firmware is provided. The method includes dividing the firmware into a plurality of sections, and assigning the sections to a plurality of block segments. The method includes generating a firmware chain by generating a series of blocks corresponding to the block segments and creating links between the blocks, and publishing the block segments onto the firmware chain. The method includes obtaining the sections from the firmware chain, and updating the sections to a first storage bank of the target device.

Method and data structure for updating firmware

An image binarization method and an electronic device using the same are provided. The method includes capturing an image by an image capturing device; selecting a target pixel row arranged at the front from one or more unselected first pixel rows among M pixel rows of the image according to a row order by a binarization circuit; performing, by the binarization circuit, a binarization operation on the target pixel row to obtain a binarized pixel row; storing the binarized pixel row to a main memory by the binarization circuit; performing, by the binarization circuit, the binarization operation to the remaining one or more first pixel rows until M binarized pixel rows are obtained, so as to complete the binarization operation.

Image binarization method and electronic device

A storage device, which is coupled to a host and a first register, includes a first mapping register, a shadow register, and a controller. The first mapping register is configured to store the first address of the first register. The shadow register includes a first shadow section mapped to a register section of the first register. The controller receives an initialization instruction generated by the host to write the first address into the first mapping register so that the first shadow section is mapped to the first register section.

Storage devices mapped to registers and mapping methods thereof

An electronic processing device including a memory and a Micro Control Unit (MCU) is provided. The memory includes a first memory block and a second memory block. The MCU executes first program code stored in the first memory block to write an update program code into the second memory block, and remaps a base address for a reboot of the electronic processing device from the first memory block to the second memory block in response to successfully writing the update program code into the second memory block. After that, the MCU triggers the reboot of the electronic processing device to execute the update program code stored in the second memory block.

Electronic processing devices and memory control methods thereof

A recognition method includes: receiving a training voice or a training image; and extracting a plurality of voice features in the training voice, or extracting a plurality of image features in the training image; wherein when extracting the voice features, a specific number of voice parameters are generated according to the voice features, and the voice parameters are input into a deep neural network (DNN) to generate a recognition model. When extracting the image features, the specific number of image parameters are generated according to the image features, and the image parameters are input into the deep neural network to generate the recognition model.

Recognition system and recognition method

An authentication system and method for an electronic governor of an unmanned aerial vehicle is disclosed. By employing reciprocative authentication and encryption mechanisms between a main control terminal and an electronic governor, the use of a modified electronic governor is prevented and thus the illegal use of UAVs is also prevented. Moreover, the provided electronic governor may be operated in dual-mode to extend its compatibility to conventional main control terminals.

Authentication system and method for electronic governor of unmanned aerial vehicle

A control circuit programming levels of pins is provided. A first slot is configured to adjust a first count value according to a clock signal. A timer controller is configured to determine whether the first count value is equal to a first predetermined value. When the first count value is equal to the first predetermined value, the timer controller generates a first trigger signal. A buffer controller is configured to access the input/output buffer. A pin controller is coupled to a first pin, the timer controller and the buffer controller. In an input mode, the pin controller detects the voltage level of the first pin according to the first trigger signal to generate a plurality of detection results. In an output mode, the pin controller generates an output signal according to the first trigger signal and output data stored in the input/output buffer.

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Taoyuan, Taiwan

Tzu-Lan Shen