Time Complexity Analysis of Recursive Algorithms Time complexity analysis of recursive algorithms helps determine how execution time grows as input size increases using recurrence relations and Big O notation. Learn how to solve recurrence relations using the substitution method, recursion tree method, and Master theorem …
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ESP32 GPIO Pins Explained: Pinout, Functions and Applications ESP32 GPIO pins support digital input/output, analog sensing, PWM control, and communication with external devices. Explore the ESP32 GPIO pin diagram, individual pin functions, pin limitations, and practical Arduino IDE examples. Learn how to select the right …
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Heap Data Structure: Types, Operations & Heap Sort A heap is a complete binary tree that follows the max heap or min heap property to organize data efficiently. Learn how heap insertion, deletion, heapify operations, and array representation work with step-by-step examples. Explore heap sort, …
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Watchdog vs Brown-Out Reset: Understanding Microcontroller Reset Mechanisms A watchdog timer detects when firmware fails to service it within the expected time, while a brown-out reset responds to an insufficient microcontroller supply voltage. STM32 microcontrollers may support watchdog mechanisms such as IWDG and WWDG, along …
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TinyML Quantization: Reduce Neural Network Size for MCUs TinyML quantization reduces neural network size by converting FP32 weights into lower-precision formats such as INT8, helping microcontrollers save memory and improve inference efficiency. Techniques such as post-training quantization and quantization-aware training help optimize models while maintaining …
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How to Reduce RAM and Flash Memory Usage in Embedded C Embedded C memory optimization helps reduce RAM consumption and Flash memory usage in resource-constrained microcontrollers. Key techniques include choosing appropriate data types, using const for read-only data, reducing array and buffer sizes, optimizing structure …
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ESP32 TensorFlow Lite Micro: Model Deployment Guide This tutorial explains how to deploy a machine learning model on ESP32 using TensorFlow Lite Micro. It covers dataset preparation, model training, TensorFlow Lite conversion, quantization, C-array generation, embedded inference, memory management, troubleshooting, and practical TinyML applications. Machine …
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