Advanced Signal Analytics
The definitive analytics infrastructure for the institutional enterprise. Engineered for the extremes of high-frequency execution and massive-scale machine learning.
VectorWave
Nanosecond latency on the JVM. Pure Java 21 core with optional Java 25 extensions for Vector API SIMD. < 100ns per-tick P50.
- Java 21 LTS + Java 25 Extensions
- DWT • MODWT • SWT • CWT
- Haar • Daubechies • Symlets • Coiflets • Biorthogonal
- Real-time streaming
IronWave
Production-ready wavelet transforms in pure Rust. Engineered for nanosecond latency with SIMD. < 100ns per-tick.
- Pure Rust • SIMD • Zero-allocation
- DWT • MODWT • SWT • CWT • WPT • EMD
- Haar • Daubechies • Symlets • Coiflets • Biorthogonal
- Real-time streaming
Key Use Cases
Signal Denoising & ML Data Prep
Precisely remove noise and extract critical features from complex signals, optimizing time series data preparation for machine learning and AI model training.
High-Frequency Trading
Execute sub-100ns streaming transforms for real-time signal analysis, enabling ultra-low latency trading strategies and tick-by-tick market microstructure analysis.
Real-time System Monitoring
Detect anomalies and monitor system health with streaming wavelet transforms for immediate insights and alerts.
Biomedical Signal Analysis
Decompose and analyze complex physiological data such as ECG, EEG, and EMG for diagnostic and research purposes.
The Modern Advantage
Cloud-Native Architecture
Eliminate the "DLL hell" and JNI bottlenecks of legacy libraries. Our pure-code implementations (Java 21+ & Rust) deploy seamlessly across modern containerized environments, from local execution to distributed Spark/Flink clusters.
Hardware-First Design
Don't settle for generic math. We explicitly target modern CPU instruction sets (AVX-512, NEON) using the Java Vector API and Rust SIMD intrinsics, unlocking performance that legacy numeric libraries cannot match.
Operational Safety
Get the speed of C++ without the catastrophic risk. IronWave's memory safety and VectorWave's structured concurrency guarantee that your trading engine stays up, even under the most extreme market conditions.
Research-Driven Engineering
Canonical Mathematical Foundations
Our algorithms are not approximations. They are rigorous implementations of the canonical literature—from Ingrid Daubechies' orthogonal wavelets to Percival & Walden's spectral analysis.
We validate every transform against reference implementations in MATLAB and R to ensure numerical precision down to the last bit.
Test-Driven Reliability
Reliability is not an afterthought. Both VectorWave and IronWave are built using strict Test-Driven Development (TDD) methodologies.
- Extensive Unit & Integration Test Suites
- Property-Based Fuzz Testing
- Cross-Platform Validation (CI/CD)
The Performance Gap
View Detailed Performance Metrics →
Wavelet Transforms for High-Frequency Trading →
Streaming Wavelet Transforms for Time-Series ML →
| Feature | MorphIQ (VectorWave/IronWave) | Legacy Libraries (IMSL/NAG) | DIY C++ / Intel IPP | Research Tools (MATLAB) |
|---|---|---|---|---|
| Architecture | Cloud-Native (Pure Java 21+ / Rust) | Legacy Wrappers (JNI/Fortran) | Low-Level Native | Interpreted / Prototyping |
| Safety | Memory-Safe / Structured | Crash-Prone (Unsafe JNI) | High Risk (Segfaults) | N/A (Runtime Errors) |
| Hardware Opt. | Vector API / SIMD Intrinsics | Generic / Outdated | Manual Tuning Required | Abstracted / Limited |
| Deployment | Seamless (Maven / Cargo) | Complex (DLLs / Lic Servers) | Complex Build Chains | Difficult (Compiler Req.) |
| Latency (Streaming) | < 100ns(Criterion-verified, zero-allocation) | > 200μs (JNI Overhead) | ~1-5μs (raw, unsafe) | > 10ms (Not production-viable) |
Related
FAQ
What makes MorphIQ analytics different from legacy libraries?
VectorWave and IronWave use streaming wavelet transforms with SIMD acceleration and memory-safe design, delivering nanosecond latency without JNI overhead.
Which library should I choose?
VectorWave targets JVM-based stacks and AI pipelines, while IronWave is optimized for Rust-native low-latency execution.
Where can I review performance benchmarks?
See the performance and benchmark methodology pages for latency and throughput results with reproducibility notes.