Forem: Md Sazzad Hissain Khan The latest articles on Forem by Md Sazzad Hissain Khan (@hissain). https://forem.com/hissain https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F291671%2F8dfc34df-533c-4aa1-bff1-9a3b748623be.jpeg Forem: Md Sazzad Hissain Khan https://forem.com/hissain en jscipy is now on Maven Central (SciPy-like signal processing library for Java) Md Sazzad Hissain Khan Sun, 01 Feb 2026 14:08:52 +0000 https://forem.com/hissain/jscipy-is-now-on-maven-central-scipy-like-signal-processing-library-for-java-37ca https://forem.com/hissain/jscipy-is-now-on-maven-central-scipy-like-signal-processing-library-for-java-37ca <p>jscipy is now on Maven Central (SciPy-like signal processing library for Java)</p> <p>I’m happy to share that jscipy has been released to Maven Central, alongside JitPack support.</p> <ul> <li>Group ID: io.github.hissain</li> <li>Artifact ID: jscipy</li> <li>Maven Central listing: <a href="https://central.sonatype.com/artifact/io.github.hissain/jscipy" rel="noopener noreferrer">https://central.sonatype.com/artifact/io.github.hissain/jscipy</a> </li> </ul> <p>jscipy aims to provide SciPy-style numerical and signal processing utilities for Java and Android, with a focus on performance and clean APIs.</p> <p>Feedback and contributions are welcome.</p> java machinelearning jSciPy: A Practical SciPy-Inspired Scientific Computing and Signal Processing Library for Java & Android Md Sazzad Hissain Khan Sat, 24 Jan 2026 20:26:12 +0000 https://forem.com/hissain/jscipy-a-practical-scipy-inspired-scientific-computing-and-signal-processing-library-for-java--334m https://forem.com/hissain/jscipy-a-practical-scipy-inspired-scientific-computing-and-signal-processing-library-for-java--334m <p>Python’s SciPy ecosystem dominates scientific computing, but Java developers working on JVM backends, Android, or embedded systems lack an equivalent, modern, signal-processing-focused library.</p> <p><strong>jSciPy</strong> aims to fill that gap.</p> <p>jSciPy is an open-source Java scientific computing and signal processing library, inspired by SciPy, designed for JVM and Android, with a strong focus on DSP, transforms, and numerical utilities.</p> <ul> <li> <strong>GitHub:</strong> <a href="https://github.com/hissain/jscipy" rel="noopener noreferrer">https://github.com/hissain/jscipy</a> </li> <li> <strong>Docs:</strong> <a href="https://hissain.github.io/jscipy" rel="noopener noreferrer">https://hissain.github.io/jscipy</a> </li> </ul> <h2> Why jSciPy Exists </h2> <p>Java has excellent general-purpose math libraries, but DSP-heavy workflows still face problems:</p> <ul> <li>No SciPy-like signal processing API in Java</li> <li>Fragmented FFT and filter implementations</li> <li>Android incompatibility of many JVM math libraries</li> <li>Heavy abstractions for simple numerical tasks</li> </ul> <h3> jSciPy focuses on practicality: </h3> <ul> <li>Minimal dependencies</li> <li>Clear APIs</li> <li>Android compatibility</li> <li>SciPy-like mental model for engineers switching ecosystems</li> </ul> <h2> Core Capabilities </h2> <h3> Signal Processing </h3> <ul> <li>FIR and IIR filters <ul> <li>Butterworth </li> <li>Chebyshev </li> <li>Elliptic </li> <li>Bessel </li> </ul> </li> <li>Zero-phase filtering </li> <li>Detrending </li> <li>Peak detection </li> <li>Median filtering </li> <li>Savitzky-Golay smoothing </li> </ul> <h3> Spectral Analysis and Transforms </h3> <ul> <li>FFT / IFFT </li> <li>STFT / ISTFT </li> <li>Hilbert Transform </li> <li>DCT / IDCT </li> <li>Spectrogram </li> <li>Periodogram </li> <li>Welch PSD estimation </li> </ul> <h3> Window Functions </h3> <ul> <li>Hann </li> <li>Hamming </li> <li>Blackman </li> <li>Rectangular </li> <li>Kaiser </li> <li>Bartlett </li> <li>Triangular </li> </ul> <h3> Numerical Utilities </h3> <ul> <li>Convolution and correlation </li> <li>Resampling </li> <li>Interpolation (linear, cubic spline) </li> <li>RK4 ODE solver </li> </ul> <h2> JVM and Android First </h2> <p>jSciPy is designed to be Android compatible and avoids heavy native dependencies, making it suitable for:</p> <ul> <li>Android applications </li> <li>Wearables </li> <li>Embedded JVM systems </li> <li>Edge devices </li> </ul> <h2> Installation (Gradle) </h2> <div class="highlight js-code-highlight"> <pre class="highlight plaintext"><code>repositories { maven { url 'https://jitpack.io' } } dependencies { implementation 'com.github.hissain:jscipy:VERSION' } </code></pre> </div> <h2> Comparison: jSciPy vs SciPy </h2> <div class="table-wrapper-paragraph"><table> <thead> <tr> <th>Feature</th> <th>SciPy (Python)</th> <th>jSciPy (Java)</th> </tr> </thead> <tbody> <tr> <td>Language</td> <td>Python</td> <td>Java</td> </tr> <tr> <td>Signal Processing</td> <td>Yes</td> <td>Yes</td> </tr> <tr> <td>FFT / STFT</td> <td>Yes</td> <td>Yes</td> </tr> <tr> <td>Welch PSD</td> <td>Yes</td> <td>Yes</td> </tr> <tr> <td>DCT</td> <td>Yes</td> <td>Yes</td> </tr> <tr> <td>Android Support</td> <td>No</td> <td>Yes</td> </tr> <tr> <td>Native Dependencies</td> <td>Often</td> <td>No</td> </tr> <tr> <td>Runtime</td> <td>CPython</td> <td>JVM</td> </tr> </tbody> </table></div> <h2> Comparison: jSciPy vs Apache Commons Math </h2> <div class="table-wrapper-paragraph"><table> <thead> <tr> <th>Aspect</th> <th>Apache Commons Math</th> <th>jSciPy</th> </tr> </thead> <tbody> <tr> <td>Focus</td> <td>General math</td> <td>Signal processing</td> </tr> <tr> <td>DSP Filters</td> <td>Limited</td> <td>Extensive</td> </tr> <tr> <td>FFT</td> <td>Basic</td> <td>Advanced</td> </tr> <tr> <td>Android Friendly</td> <td>Mixed</td> <td>Yes</td> </tr> <tr> <td>SciPy-like API</td> <td>No</td> <td>Yes</td> </tr> </tbody> </table></div> <h2> Comparison: jSciPy vs EJML </h2> <div class="table-wrapper-paragraph"><table> <thead> <tr> <th>Aspect</th> <th>EJML</th> <th>jSciPy</th> </tr> </thead> <tbody> <tr> <td>Focus</td> <td>Linear algebra</td> <td>Signal processing</td> </tr> <tr> <td>FFT</td> <td>No</td> <td>Yes</td> </tr> <tr> <td>Filters</td> <td>No</td> <td>Yes</td> </tr> <tr> <td>DSP Tools</td> <td>No</td> <td>Yes</td> </tr> <tr> <td>Matrix Operations</td> <td>Excellent</td> <td>Minimal</td> </tr> </tbody> </table></div> <h2> Typical Use Cases </h2> <ul> <li>Audio signal processing on JVM </li> <li>EEG and ECG analysis </li> <li>Android sensor data processing </li> <li>Embedded DSP pipelines </li> </ul> <h2> Design Philosophy </h2> <ul> <li>Clarity over abstraction </li> <li>Practical DSP focus </li> <li>Minimal dependencies </li> <li>Engineering-first design </li> </ul> <h2> Final Thoughts </h2> <p>If you work with signal processing on Java or Android, jSciPy provides a practical, SciPy-inspired toolkit that has been missing from the JVM ecosystem.</p> <ul> <li> <strong>GitHub:</strong> <a href="https://github.com/hissain/jscipy" rel="noopener noreferrer">https://github.com/hissain/jscipy</a> </li> <li> <strong>Docs:</strong> <a href="https://hissain.github.io/jscipy" rel="noopener noreferrer">https://hissain.github.io/jscipy</a> </li> </ul> java machinelearning