VectorWave
Java 21 LTSJava 25 ExtensionsHigh-Performance Wavelet Transforms for the Modern JVM
VectorWave delivers nanosecond latency on the JVM—a feat previously thought impossible. The secret: O(L) incremental streaming algorithms that achieve sub-100ns latency through mathematical optimization, not just hardware acceleration. Production-ready on Java 21 LTS with bleeding-edge extensions for Java 25—including Vector API SIMD acceleration and structured concurrency.
Nanosecond Latency
< 100ns P50 latency—nanosecond-scale performance in pure Java 21, no native code required. Java 25 extensions unlock SIMD acceleration.
MODWT & SWT
Shift-invariant discrete transforms on signals of any length. No power-of-2 restrictions. Perfect reconstruction guaranteed.
CWT Analysis
FFT-accelerated continuous transforms with 17 wavelets: Morlet, Mexican Hat, Gaussian derivatives, Shannon, Meyer, and more.
Wavelet Families
Haar, Daubechies (db2-db20), Symlets, Coiflets, Biorthogonal, and specialized financial wavelets for market analysis.
Real-Time Streaming
Incremental O(L) decomposition for continuous data streams. Arbitrary block sizes with microsecond latency.
Enterprise Ready
Zero dependencies. Integrates with Spark, Flink, and financial platforms. Java 25 adds structured concurrency.
Accelerating AI & Machine Learning Pipelines
Big Data & Spark Integration
Process terabytes of training data efficiently using SIMD-accelerated batch operations compatible with Apache Spark, Flink, and Hadoop ecosystems.
Robust Feature Engineering
Extract statistically stable, shift-invariant features using MODWT to improve model convergence and predictive accuracy in time-series forecasting.
Noise Reduction for Training
Apply advanced denoising techniques to prepare cleaner, high-fidelity datasets, essential for training sensitive Deep Learning models.