signal

ANNOY YOURSELF INTO BETTER DRIVING WITH THIS TURN SIGNAL MONITOR

ANNOY YOURSELF INTO BETTER DRIVING WITH THIS TURN SIGNAL MONITOR

Something like 99% of the people on the road at any given moment will consider themselves an above-average driver, something that’s as statistically impossible as it is easily disproven by casual observation. Drivers make all kinds of mistakes, but perhaps none as annoying and avoidable as failure to use their turn signal. This turn signal

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A NIXIE CLOCK THE HARD WAY

A NIXIE CLOCK, THE HARD WAY

Notice: no vintage Hewlett Packard test equipment was harmed in the making of this overly complicated Nixie clock. In fact, if anything, the HP 5245L electronic counter came out better off than it went into the project. We mention the fate of this instrument mainly because we’ve seen our fair share of cool-looking-old-thing-gutted-and-filled-with-Arduinos projects before, and

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3.3V 3A WIDE INPUT SYNCHRONOUS STEP DOWN DC DC REFERENCE DESIGN

3.3V/3A, WIDE-INPUT, SYNCHRONOUS, STEP-DOWN DC-DC REFERENCE DESIGN

The MAXREFDES1048 synchronous step-down dc-dc converter reference design from Maxim Integrated Products is based on the MAX17504, a high-efficiency, high-voltage, synchronously rectified step-down converter with dual integrated MOSFETs can operate over a 4.5V to 60V input. The MAXREFDES1048 reference design operates over an input voltage range of 18- to 36-Vdc and delivers an output of 3A. The MAX17504 can deliver up to

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ESP32 S2 PROCESSOR DATASHEET RELEASED DEVELOPMENT BOARDS UNVEILED

ESP32-S2 PROCESSOR DATASHEET RELEASED, DEVELOPMENT BOARDS UNVEILED

Since the launch of the ESP-01, the ESP series of WiFi modules and WiFi-enabled microcontrollers have endeared themselves to the heart of both hobbyist and electronics design professionals. They have been used for all sorts of projects and while users are still praising the impressive features built into its most recent version, the ESP-32, Espressif systems have announced details

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Sample Model

Arduino Sketch Classifier Demo

N.B. this is new and still being tested. This sketch demonstrates an example of ultrasonic range sensor data processing using a combination of signal filters and a classification tree. The classifier code was generated using the Python script classify_gen.py on recorded and labeled training data. The underlying classification tree was automatically generated using the Python scikit-learn library. For more

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