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// author: fangjun kuang <csukuangfj at gmail dot com>
// date: Apr. 22, 2019

// refer to http://www.topherlee.com/software/pcm-tut-wavformat.html

#include <fstream>
#include <iostream>
typedef struct WAV_HEADER {
  /* RIFF Chunk Descriptor */

csukuangfj

STM32 MacOS X Environment Setup

Table of Contents

• 1. Install JDK 8
• 2. Install Eclipse
  • Option 1: GNU MCU Eclipse IDE for C/C++ Developers
• 3. Cross Compile Toolchain (arm-none-eabi-*))
  • Option 1: GNU MCU Eclipse ARM Embedded GCC

• Option 2: GNU ARM Embedded Toolchain

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Linking libstdc++ statically
Christopher Baus writes about his problems linking libstdc++ statically. Yes, making C++ binaries that will work properly in different Linux distributions is somewhat painful. The problem is not so much linking libstdc++ statically – it is just a library, after all – but the runtime support required by C++ code in general, to enable features like RTTI and exception handling.

The runtime support code used by different parts of a C++ application needs to be compatible. If one part of the program needs to dynamic_cast or catch objects provided by another, both parts must agree on certain implementation details: how to find vtables, how to unwind the stack, and so on.

For C++ and a few other GCC-supported languages with similar features, such details are specified by a C++ ABI. Whenever the ABI used by GCC changes you'll end up with incompatible libraries produced by the different GCC versions. The same is true for plain C, but the C ABI is much simpler and has been around a lot lon

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// This example shows how to create
// a context from a specified device type
// using OpenCL wrappers provided by OpenCV 3.x
//
// The default platform is the zero-th platform
// returned by clGetPlatformIDs.
//
// To compile it on Mac OS X, add `-framework opencl`
// to CXX_FLAGS

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// Copyright 2017. All Rights Reserved.
// Author: csukuangfj@gmail.com (Fangjun Kuang)

#include <QtGui>
#include <QGraphicsRectItem>
#include <QGraphicsView>
#include <QApplication>
#include <QGraphicsSceneMouseEvent>

class CustomItem : public QGraphicsEllipseItem

csukuangfj

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

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ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz:

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GNU ld (GNU Binutils for Ubuntu) 2.25.1
  Supported emulations:
   elf_x86_64
   elf32_x86_64
   elf_i386
   i386linux
   elf_l1om
   elf_k1om
   i386pep
   i386pe

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#!/usr/bin/env python3

# Copyright (c)  2021  Xiaomi Corporation (authors: Fangjun Kuang)

from snowfall.training.ctc_graph import build_ctc_topo2
from speechbrain.pretrained import EncoderDecoderASR

import k2
import torch

csukuangfj

Deep Learning

• https://github.com/ARM-software/CMSIS_5/blob/develop/CMSIS/NN/Include/arm_nnfunctions.h
• a paper [CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs][1], google scolar of the author [Liangzhen Lai][2]
• a paper [Fixed point quantization of deep convolutional networks][3]
• a paper [Deep Convolutional Neural Network Inference with Floating-point Weights and Fixed-point Activations][4]
• a blog [Why GEMM is at the heart of deep learning][5]
• a paper [cuDNN: Efficient Primitives for Deep Learning][6]