Fast trainable multidimensional IIR filter layers in TensorFlow
Project description
IIRD: Fast Trainable Multidimensional IIR Filter Layers in TensorFlow
IIRD provides trainable 1D, 2D, and 3D IIR filter layers for TensorFlow/Keras.
Copyright 2025 Kishore Kumar Tarafdar.
Licensed under the Apache License, Version 2.0. See LICENSE.
Capabilities
IIR1D,IIR2D, andIIR3DKeras layers.- Trainable feedforward and feedback coefficients.
- Batched multichannel TensorFlow tensors.
- Frequency-response plotting utility.
Minimal Example
import tensorflow as tf
from IIRD import IIR1D, IIR2D, IIR3D
x1 = tf.random.normal([1, 64, 1])
y1 = IIR1D(Delays=2, filters=4)(x1)
x2 = tf.random.normal([1, 32, 32, 1])
y2 = IIR2D(Delays=2, filters=4)(x2)
x3 = tf.random.normal([1, 16, 16, 16, 1])
y3 = IIR3D(Delays=1, filters=2)(x3)
print(y1.shape, y2.shape, y3.shape)
Module Commands
python -m IIRD.IIR1D
python -m IIRD.IIR2D
python -m IIRD.IIR3D
Citation
This software is released for broad research, educational, and engineering use. If this package helps your work, please cite the following paper:
@misc{tarafdar2026interpretablefrugallearningsystems,
title={Interpretable and Frugal Learning Systems Employing Multiresolution Pyramids and Volterra Kernels},
author={Kishore Kumar Tarafdar},
year={2026},
eprint={2606.15011},
archivePrefix={arXiv},
primaryClass={eess.SP},
url={https://arxiv.org/abs/2606.15011},
}
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