由simon haykin著作。对海杂波有兴趣的人适用

Tensorflow QRNN TensorFlow的QRNN实现。 实现参考下面的博客。 依存关系 TensorFlow：0.12.0 scikit-learn：0.18.1（用于工作检查） 怎么跑 向前测试 要确认正向传播，请运行以下脚本。 python test_tf_qrnn_forward.py 工作检查 要确认QRNN与基准（LSTM）的性能比较，请运行以下脚本。 数据集是。 python test_tf_qrnn_work.py 您可以通过查看计算结果。 例如。 tensorboard --logdir=./summary/qrnn 实验 Baseline(LSTM)

kmbox：MatlabOctave的内核方法工具箱

国外经典的遥感教程,入门和提升的必修之作，国内遥感领域大师推荐的教程，指的一看。

CLIP图像分类 使用 from classify import load , classify filename = "/content/input.jpg" load_categories = "imagenet" print ( "loading categories" ) load ( load_categories ) print ( "classifying" ) print ( classify ( filename )) load load ( "imagenet" ) #imagenet categories load ( "pokemon" ) #loads a list of 721 pokemon names as categories load ( "dog vs cat" ) #dog and cat as categories load ( "words i

Digital Image Processing 4th Edition [Rafael C. Gonzalez]

Design and Implementation of small microphone arrays

雷达信号处理基础（第二版） 雷达信号处理基础（第二版）

This book by Ivan Tashev provides a comprehensive yet concise overview of the fundamental problems and core signal processing algorithms for digital sound capture, including ambient noise reduction, acoustic echo cancellation, and reduction of reverberation. After introducing the necessary basic aspects of digital audio signal processing, the book presents basic physical properties of sound and propagation of sound waves, as well as a review of microphone technologies, providing the reader with a strong understanding of key aspects of digitized sounds. The book discusses the fundamental problems of noise reduction, which are usually solved via techniques based on statistical models of the signals of interest (typically voice) and of interfering signals. An important discussion of properties of the human auditory system is also presented; auditory models can play a very important role in algorithms for enhancing audio signals in communication and recording/playback applications, where the final destination is the human ear.

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