diff --git a/Denoising Sine wave signal/Dataset/README.md b/Denoising Sine wave signal/Dataset/README.md new file mode 100644 index 000000000..c713ce848 --- /dev/null +++ b/Denoising Sine wave signal/Dataset/README.md @@ -0,0 +1,25 @@ +# Dataset for Signal Denoising Autoencoder + +This dataset contains synthetic or real-world signals with added noise, used for training and testing a denoising autoencoder. It includes columns representing the original amplitude of the signal and the noisy version of the signal. + +## Dataset Structure + +The dataset file (`ex1.xlsx`) includes the following columns: +- **Amplitude**: The original, clean signal amplitude. +- **Amplitude_noise**: The amplitude of the signal after noise has been added. + +The data is sequential and each entry represents one time step. + +### Loading the Dataset +To load the dataset in Python, use the following code: + +```bash +import pandas as pd + +data = pd.read_excel('ex1.xlsx') +original_amplitude = data['Amplitude'].values +noised_amplitude = data['Amplitude_noise'].values +``` + +### Usage +This dataset is used to train and evaluate denoising models, which will learn to filter noise from signals, providing a cleaned signal that approximates the original. \ No newline at end of file diff --git a/Denoising Sine wave signal/Dataset/ex1.xlsx b/Denoising Sine wave signal/Dataset/ex1.xlsx new file mode 100644 index 000000000..5fcd84ed0 Binary files /dev/null and b/Denoising Sine wave signal/Dataset/ex1.xlsx differ diff --git a/Denoising Sine wave signal/Images/Result_image.png b/Denoising Sine wave signal/Images/Result_image.png new file mode 100644 index 000000000..c36c7e3cd Binary files /dev/null and b/Denoising Sine wave signal/Images/Result_image.png differ diff --git a/Denoising Sine wave signal/Model/README.md b/Denoising Sine wave signal/Model/README.md new file mode 100644 index 000000000..193c78ba9 --- /dev/null +++ b/Denoising Sine wave signal/Model/README.md @@ -0,0 +1,119 @@ +# Sine Wave Signal Denoising + +## Project Overview + +This project demonstrates how to denoise a noisy signal using deep learning models, primarily through a Convolutional Autoencoder, LSTM Autoencoder, and an enhanced Conv1D Autoencoder. Each model is designed to take a noisy signal as input and reconstruct the original (denoised) signal. After denoising, the Savitzky-Golay filter is applied to further smooth the output. + +### Methodology + +1. **Preprocessing**: + - The signal is normalized using `MinMaxScaler`. + - Both noisy and original signals are reshaped into sliding windows for training. + +2. **Model Architectures**: + - **Conv1D Autoencoder**: A Convolutional Autoencoder built to map noisy signals to clean ones, using convolutional and pooling layers for feature extraction and dimensionality reduction. + - **LSTM Autoencoder**: A recurrent model utilizing LSTM layers to capture temporal dependencies, effective for time-series data. + - **Enhanced Conv1D Autoencoder**: An improved version of the Conv1D Autoencoder with deeper layers for better feature extraction and reconstruction capabilities. + +3. **Postprocessing**: + - The Savitzky-Golay filter is applied to the output to further reduce residual noise. + +4. **Visualization**: + - The original, noisy, and denoised signals are plotted for a comprehensive visual comparison. + +### Dependencies + +- Python 3.x +- `pandas` +- `numpy` +- `scikit-learn` +- `tensorflow` +- `scipy` +- `matplotlib` + +### Installation + +1. Clone the repository: + ```bash + git clone https://github.com/yourusername/signal denoising autoencoder.git + ``` + +2. Install dependencies: + ```bash + pip install -r requirements.txt + ``` + +### Usage + +1. Prepare your dataset in an Excel file (`ex1.xlsx`) with two columns: `Amplitude` and `Amplitude_noise`. + +2. Run the denoising script: + ```bash + python denoise_signal.py + ``` + +3. The script will train the autoencoders on the noisy signal, output the denoised signals, and plot them alongside the original and noisy signals. + +### Model Details + +#### Conv1D Autoencoder + +The model architecture: +``` +Layer (type) Output Shape Param # +================================================================= +input_signal (InputLayer) [(None, 4500, 1)] 0 +_________________________________________________________________ +conv1d (Conv1D) (None, 4500, 16) 64 +_________________________________________________________________ +max_pooling1d (MaxPooling1D) (None, 2250, 16) 0 +_________________________________________________________________ +conv1d_1 (Conv1D) (None, 2250, 8) 392 +_________________________________________________________________ +max_pooling1d_1 (MaxPooling1D) (None, 1125, 8) 0 +_________________________________________________________________ +conv1d_2 (Conv1D) (None, 1125, 8) 200 +_________________________________________________________________ +up_sampling1d (UpSampling1D) (None, 2250, 8) 0 +_________________________________________________________________ +conv1d_3 (Conv1D) (None, 2250, 16) 400 +_________________________________________________________________ +up_sampling1d_1 (UpSampling1D) (None, 4500, 16) 0 +_________________________________________________________________ +conv1d_4 (Conv1D) (None, 4500, 1) 49 +================================================================= +Total params: 1,105 +Trainable params: 1,105 +Non-trainable params: 0 +``` + +#### LSTM Autoencoder + +The LSTM Autoencoder captures sequential dependencies, which is particularly effective for time-series data. This model consists of: +- A stack of LSTM layers for encoding the sequence. +- An intermediate dense layer for feature extraction. +- LSTM layers for decoding the signal back to its denoised form. + +The model is effective for denoising tasks with complex temporal dependencies and uses `Mean Squared Error (MSE)` as the loss function. + +#### Enhanced Conv1D Autoencoder + +An advanced convolutional model that expands upon the basic Conv1D Autoencoder: +- Deeper architecture with additional convolutional layers for enhanced feature extraction. +- Additional UpSampling and convolutional layers for improved reconstruction capabilities. +- MaxPooling and UpSampling for dimensionality adjustments and noise removal, offering better denoising for high-frequency noise. + +### Results + +After training each model, the denoised signals are plotted and visually compared with the original and noisy signals. Each model significantly reduces noise, preserving the main structure of the original signal. + +### Comparison of Model Performance + +- **Conv1D Autoencoder**: Ideal for signals with moderate noise levels; balances simplicity and accuracy. +- **LSTM Autoencoder**: Better suited for sequential data, capturing dependencies over longer periods. +- **Enhanced Conv1D Autoencoder**: Offers the best denoising performance among the models due to its deeper architecture and robust feature extraction capabilities. + +### Conclusion + +This project demonstrates how deep learning models, particularly convolutional and recurrent autoencoders, can be used for signal denoising. Further improvements can be made by experimenting with model architectures, window sizes, and smoothing techniques to enhance the denoising process. + diff --git a/Denoising Sine wave signal/Model/denoise_signal.ipynb b/Denoising Sine wave signal/Model/denoise_signal.ipynb new file mode 100644 index 000000000..332ec60c4 --- /dev/null +++ b/Denoising Sine wave signal/Model/denoise_signal.ipynb @@ -0,0 +1,367 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "s-SbSGeiiHWW" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", + "import tensorflow as tf\n", + "from tensorflow.keras.models import Model\n", + "from tensorflow.keras.layers import Input, Conv1D, MaxPooling1D, UpSampling1D, LSTM, RepeatVector\n", + "\n", + "# Load data\n", + "data = pd.read_excel('ex1.xlsx')\n", + "original_amplitude = data['Amplitude'].values\n", + "noised_amplitude = data['Amplitude_noise'].values\n", + "\n", + "# Reshape and scale data\n", + "original_amplitude = original_amplitude.reshape(-1, 1)\n", + "noised_amplitude = noised_amplitude.reshape(-1, 1)\n", + "\n", + "scaler = MinMaxScaler()\n", + "original_amplitude = scaler.fit_transform(original_amplitude)\n", + "noised_amplitude = scaler.transform(noised_amplitude)\n", + "\n", + "# Windowing function\n", + "window_size = 4500\n", + "\n", + "def create_windows(data, window_size):\n", + " windows = []\n", + " for i in range(len(data) - window_size + 1):\n", + " windows.append(data[i:i + window_size])\n", + " return np.array(windows)\n", + "\n", + "X = create_windows(noised_amplitude, window_size)\n", + "y = create_windows(original_amplitude, window_size)\n", + "\n", + "# Reshape for training\n", + "X_train = X.reshape(-1, window_size, 1)\n", + "y_train = y.reshape(-1, window_size, 1)\n" + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "# Conv1D Autoencoder Model\n", + "input_signal = Input(shape=(window_size, 1))\n", + "x = Conv1D(16, 3, activation='relu', padding='same')(input_signal)\n", + "x = MaxPooling1D(2, padding='same')(x)\n", + "x = Conv1D(8, 3, activation='relu', padding='same')(x)\n", + "encoded = MaxPooling1D(2, padding='same')(x)\n", + "\n", + "x = Conv1D(8, 3, activation='relu', padding='same')(encoded)\n", + "x = UpSampling1D(2)(x)\n", + "x = Conv1D(16, 3, activation='relu', padding='same')(x)\n", + "x = UpSampling1D(2)(x)\n", + "decoded = Conv1D(1, 3, activation='relu', padding='same')(x)\n", + "\n", + "autoencoder = Model(input_signal, decoded)\n", + "autoencoder.compile(optimizer='adam', loss='mean_squared_error')\n", + "\n", + "# Train Conv1D Autoencoder\n", + "autoencoder.fit(X_train, y_train, epochs=20, batch_size=64, validation_split=0.2)\n", + "denoised_signal = autoencoder.predict(X_train)\n", + "denoised_signal = scaler.inverse_transform(denoised_signal.reshape(-1, 1))\n" + ], + "metadata": { + "id": "O8zgduNziMZj", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "3ad4a175-9ea0-4cc3-b5e1-e2f590407e03" + }, + "execution_count": 8, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 370ms/step - loss: 0.2526 - val_loss: 0.1544\n", + "Epoch 2/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 301ms/step - loss: 0.1244 - val_loss: 0.0546\n", + "Epoch 3/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 393ms/step - loss: 0.0425 - val_loss: 0.0270\n", + "Epoch 4/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 198ms/step - loss: 0.0293 - val_loss: 0.0291\n", + "Epoch 5/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 198ms/step - loss: 0.0268 - val_loss: 0.0188\n", + "Epoch 6/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 201ms/step - loss: 0.0187 - val_loss: 0.0167\n", + "Epoch 7/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 195ms/step - loss: 0.0150 - val_loss: 0.0092\n", + "Epoch 8/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 330ms/step - loss: 0.0084 - val_loss: 0.0042\n", + "Epoch 9/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 281ms/step - loss: 0.0038 - val_loss: 0.0019\n", + "Epoch 10/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 196ms/step - loss: 0.0022 - val_loss: 0.0020\n", + "Epoch 11/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 198ms/step - loss: 0.0023 - val_loss: 0.0019\n", + "Epoch 12/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 196ms/step - loss: 0.0020 - val_loss: 0.0016\n", + "Epoch 13/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 199ms/step - loss: 0.0019 - val_loss: 0.0016\n", + "Epoch 14/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 200ms/step - loss: 0.0018 - val_loss: 0.0015\n", + "Epoch 15/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 324ms/step - loss: 0.0017 - val_loss: 0.0014\n", + "Epoch 16/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 308ms/step - loss: 0.0016 - val_loss: 0.0014\n", + "Epoch 17/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 198ms/step - loss: 0.0016 - val_loss: 0.0013\n", + "Epoch 18/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 199ms/step - loss: 0.0015 - val_loss: 0.0013\n", + "Epoch 19/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 200ms/step - loss: 0.0015 - val_loss: 0.0013\n", + "Epoch 20/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 200ms/step - loss: 0.0014 - val_loss: 0.0012\n", + "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 43ms/step\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "# LSTM Autoencoder Model\n", + "input_signal_lstm = Input(shape=(window_size, 1))\n", + "encoded_lstm = LSTM(64, activation='relu', return_sequences=True)(input_signal_lstm)\n", + "encoded_lstm = LSTM(32, activation='relu', return_sequences=False)(encoded_lstm)\n", + "\n", + "decoded_lstm = RepeatVector(window_size)(encoded_lstm)\n", + "decoded_lstm = LSTM(32, activation='relu', return_sequences=True)(decoded_lstm)\n", + "decoded_lstm = LSTM(64, activation='relu', return_sequences=True)(decoded_lstm)\n", + "decoded_lstm = Conv1D(1, 3, activation='relu', padding='same')(decoded_lstm)\n", + "\n", + "lstm_autoencoder = Model(input_signal_lstm, decoded_lstm)\n", + "lstm_autoencoder.compile(optimizer='adam', loss='mean_squared_error')\n", + "\n", + "# Train LSTM Autoencoder\n", + "lstm_autoencoder.fit(X_train, y_train, epochs=20, batch_size=64, validation_split=0.2)\n", + "denoised_signal_lstm = lstm_autoencoder.predict(X_train)\n", + "denoised_signal_lstm = scaler.inverse_transform(denoised_signal_lstm.reshape(-1, 1))\n" + ], + "metadata": { + "id": "sZycHUhyigEk", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "546f8223-9b10-4a4f-90ed-7681141d2222" + }, + "execution_count": 4, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m123s\u001b[0m 16s/step - loss: 0.3451 - val_loss: 0.2366\n", + "Epoch 2/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m109s\u001b[0m 16s/step - loss: 0.2043 - val_loss: 0.1304\n", + "Epoch 3/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m146s\u001b[0m 16s/step - loss: 0.1466 - val_loss: 0.1301\n", + "Epoch 4/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m140s\u001b[0m 16s/step - loss: 0.1371 - val_loss: 0.1301\n", + "Epoch 5/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m141s\u001b[0m 16s/step - loss: 0.1329 - val_loss: 0.1283\n", + "Epoch 6/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m141s\u001b[0m 16s/step - loss: 0.1305 - val_loss: 0.1280\n", + "Epoch 7/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m144s\u001b[0m 16s/step - loss: 0.1282 - val_loss: 0.1276\n", + "Epoch 8/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m110s\u001b[0m 16s/step - loss: 0.1269 - val_loss: 0.1275\n", + "Epoch 9/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 16s/step - loss: 0.1258 - val_loss: 0.1279\n", + "Epoch 10/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m114s\u001b[0m 16s/step - loss: 0.1257 - val_loss: 0.1278\n", + "Epoch 11/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m137s\u001b[0m 16s/step - loss: 0.1256 - val_loss: 0.1276\n", + "Epoch 12/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 16s/step - loss: 0.1256 - val_loss: 0.1276\n", + "Epoch 13/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m110s\u001b[0m 16s/step - loss: 0.1257 - val_loss: 0.1276\n", + "Epoch 14/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 16s/step - loss: 0.1255 - val_loss: 0.1277\n", + "Epoch 15/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m144s\u001b[0m 16s/step - loss: 0.1255 - val_loss: 0.1276\n", + "Epoch 16/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m109s\u001b[0m 16s/step - loss: 0.1256 - val_loss: 0.1276\n", + "Epoch 17/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m143s\u001b[0m 16s/step - loss: 0.1255 - val_loss: 0.1276\n", + "Epoch 18/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 16s/step - loss: 0.1254 - val_loss: 0.1276\n", + "Epoch 19/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m110s\u001b[0m 16s/step - loss: 0.1256 - val_loss: 0.1276\n", + "Epoch 20/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 16s/step - loss: 0.1255 - val_loss: 0.1277\n", + "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m27s\u001b[0m 2s/step\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from tensorflow.keras.models import Model\n", + "from tensorflow.keras.layers import Input, Conv1D, MaxPooling1D, UpSampling1D\n", + "from tensorflow.keras.optimizers import Adam\n", + "\n", + "# Define the input layer\n", + "input_signal = Input(shape=(4500, 1))\n", + "\n", + "# Build the convolutional layers\n", + "x = Conv1D(16, kernel_size=3, activation='relu', padding='same')(input_signal)\n", + "x = MaxPooling1D(pool_size=2, padding='same')(x)\n", + "x = Conv1D(8, kernel_size=3, activation='relu', padding='same')(x)\n", + "encoded = MaxPooling1D(pool_size=2, padding='same')(x)\n", + "\n", + "# Build the upsampling layers\n", + "x = Conv1D(8, kernel_size=3, activation='relu', padding='same')(encoded)\n", + "x = UpSampling1D(size=2)(x)\n", + "x = Conv1D(16, kernel_size=3, activation='relu', padding='same')(x)\n", + "x = UpSampling1D(size=2)(x)\n", + "decoded = Conv1D(1, kernel_size=3, activation='relu', padding='same')(x)\n", + "\n", + "# Compile the model\n", + "conv2_autoencoder = Model(inputs=input_signal, outputs=decoded)\n", + "conv2_autoencoder.compile(optimizer=Adam(), loss='mean_squared_error')\n", + "\n", + "# Train the model\n", + "conv2_autoencoder.fit(X_train, y_train, epochs=20, batch_size=64, validation_split=0.2)\n", + "denoised_signal_conv2 = conv2_autoencoder.predict(X_train)\n" + ], + "metadata": { + "id": "S6IqOfWOijKw", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "f857b157-26a3-4f23-f7c2-43609ba4eaf0" + }, + "execution_count": 10, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Epoch 1/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 234ms/step - loss: 0.3319 - val_loss: 0.2741\n", + "Epoch 2/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 194ms/step - loss: 0.2456 - val_loss: 0.1772\n", + "Epoch 3/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 195ms/step - loss: 0.1488 - val_loss: 0.0755\n", + "Epoch 4/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 194ms/step - loss: 0.0585 - val_loss: 0.0341\n", + "Epoch 5/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 320ms/step - loss: 0.0380 - val_loss: 0.0439\n", + "Epoch 6/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 197ms/step - loss: 0.0408 - val_loss: 0.0285\n", + "Epoch 7/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 196ms/step - loss: 0.0280 - val_loss: 0.0283\n", + "Epoch 8/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 193ms/step - loss: 0.0274 - val_loss: 0.0243\n", + "Epoch 9/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 195ms/step - loss: 0.0231 - val_loss: 0.0205\n", + "Epoch 10/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 194ms/step - loss: 0.0201 - val_loss: 0.0176\n", + "Epoch 11/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 201ms/step - loss: 0.0169 - val_loss: 0.0143\n", + "Epoch 12/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 275ms/step - loss: 0.0134 - val_loss: 0.0094\n", + "Epoch 13/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 324ms/step - loss: 0.0083 - val_loss: 0.0052\n", + "Epoch 14/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 195ms/step - loss: 0.0046 - val_loss: 0.0024\n", + "Epoch 15/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 195ms/step - loss: 0.0023 - val_loss: 0.0016\n", + "Epoch 16/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 194ms/step - loss: 0.0019 - val_loss: 0.0016\n", + "Epoch 17/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 194ms/step - loss: 0.0018 - val_loss: 0.0014\n", + "Epoch 18/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 198ms/step - loss: 0.0016 - val_loss: 0.0014\n", + "Epoch 19/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 323ms/step - loss: 0.0015 - val_loss: 0.0013\n", + "Epoch 20/20\n", + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 199ms/step - loss: 0.0014 - val_loss: 0.0013\n", + "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 43ms/step\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "# Visualization\n", + "time_steps = np.arange(len(data))\n", + "plt.figure(figsize=(15, 10))\n", + "plt.plot(time_steps, data['Amplitude'], label='Original Amplitude')\n", + "plt.plot(time_steps, data['Amplitude_noise'], label='Noised Amplitude')\n", + "plt.plot(time_steps, denoised_signal.flatten()[:len(data)], label='Conv1D Autoencoder Denoised')\n", + "plt.plot(time_steps, denoised_signal_lstm.flatten()[:len(data)], label='LSTM Autoencoder Denoised')\n", + "plt.plot(time_steps, denoised_signal_conv2.flatten()[:len(data)], label='Enhanced Conv1D Autoencoder Denoised')\n", + "\n", + "plt.xlabel('Time Steps')\n", + "plt.ylabel('Amplitude')\n", + "plt.title('Signal Denoising Comparison')\n", + "plt.legend()\n", + "plt.show()\n" + ], + "metadata": { + "id": "I0AQsXgFimiV", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 858 + }, + "outputId": "d6789a3d-68ea-448d-c181-77b870a5409d" + }, + "execution_count": 11, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "qIye3gMiRYhq" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/Denoising Sine wave signal/requirements.txt b/Denoising Sine wave signal/requirements.txt new file mode 100644 index 000000000..57b782a72 --- /dev/null +++ b/Denoising Sine wave signal/requirements.txt @@ -0,0 +1,6 @@ +pandas==1.5.3 +numpy==1.23.5 +scikit-learn==1.1.2 +tensorflow==2.10.0 +scipy==1.10.0 +matplotlib==3.6.3