blinear 0.3.3

Bilinear Neural Network Library

blinear

Bilinear Neural Network Library for Deep Learning and Biomedical Signal Classification.

blinear provides custom bilinear neural network layers and hybrid CNN–bilinear architectures built with TensorFlow/Keras. The library focuses on nonlinear feature interaction modeling using Hirota-inspired bilinear operators for signal processing, sequence learning, and classification tasks.

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Features

• Hirota Bilinear Layer
• Convolutional Hirota Bilinear Layer
• OGD-based Bilinear Classification Layer
• CNN + Bilinear Hybrid Models
• Double Bilinear Architectures
• Binary and Multiclass Classification Support
• TensorFlow / Keras Compatible

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Installation

pip install blinear

1. Hirota CNN Model

CNN feature extraction followed by a Hirota bilinear interaction block.

Usage

from blinear import BilinearLayer

2. ConvHirota Bilinear Model

End-to-end convolutional bilinear feature extraction using ConvHirotaBilinear.

Usage

from blinear import ConvBilinear

3. Online Gradient Descent (OGD) Layer Guide

The OGDLayer in blinear is a deep bilinear representation layer designed for multiclass classification tasks.

from blinear import OGDLayer

Requirements

• Python >= 3.9
• TensorFlow >= 2.x
• NumPy

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License

MIT License

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Author

Developed for nonlinear bilinear deep learning research and biomedical AI applications.