🧠 RNN in C

This is a simple implementation of a Recurrent Neural Network (RNN) in pure C.
It demonstrates the concept of forward propagation over a sequence of time-series inputs without using any external libraries.

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📁 Project Structure

rnn-c/
├── include/             # Header files
│   ├── rnn.h            # RNN structure and declarations
│   └── utils.h          # Utility functions (e.g., matrix multiplication)
├── src/                 # Source code
│   ├── rnn.c            # RNN logic (init, forward, print)
│   └── utils.c          # Math utility implementation
├── data/                # Example input data (optional)
│   └── sample_input.txt
├── main.c               # Program entry point
├── Makefile             # Build configuration
└── README.md            # This file

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🧪 Requirements

• GCC or compatible C compiler (e.g. gcc, clang)
• make (for building the project)

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⚙️ Build Instructions

1. Clone or download the project:

git clone https://github.com/nomadsdev/rnn-model-with-c.git
cd rnn-c

2. Build the project using make:

make

This compiles all .c files and generates an executable named rnn.

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🚀 Running the Program

./rnn

Expected Output:

Time step 0: Output: 0.4938
Time step 1: Output: 0.4962
Time step 2: Output: 0.4975

The program performs forward propagation across 3 time steps using a hardcoded input sequence (0.1, 0.5, 0.9) and prints the output of the RNN at each step.

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🧰 How to Modify Inputs

To change the input sequence:

1. Open main.c
2. Modify the inputs[] array:

float inputs[] = {0.2f, 0.4f, 0.6f, 0.8f};

3. Rebuild the project:

make clean && make
./rnn

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🛠️ How to Extend This Project

Here are some ideas for improving this base project:

• ✅ Add Backpropagation Through Time (BPTT)
• 📉 Loss function and training loop
• 📁 Load input from file (sample_input.txt)
• 🧠 Increase model complexity (e.g., stacked RNN layers)
• 💾 Save and load weights to/from file