ANNET Technology
Eliminating A/D and D/A conversions by processing data directly in analog form. Experience 50x higher speed, 5x lower power consumption, and 100x lower latency.
Revolutionary Performance
50x faster
Speed Improvement
5x lower
Power Consumption
100x lower
Latency Reduction
Significantly lower
Cost Efficiency
Fundamental Principles
Universal Approximators
Second-generation analog neural networks are universal approximators that can approximate any continuous analog function with a single hidden-layer artificial neural network. This enables direct processing of complex analog signals.
- Continuous analog function approximation
- Single hidden-layer capability
- Direct signal processing
- No quantization errors
Continuous Time Processing
ANNET treats time as a continuous variable, eliminating the need for clocks and counters while enabling temporal integration similar to biological neural networks. This results in truly real-time processing capabilities.
- Clock-free operation
- Biological-inspired temporal integration
- Continuous time variable
- Natural parallelism
Architectural Components
Analog Memory (aMEM)
Stores weights, bias values, inputs, and outputs as analog voltages.
Key Features:
- Higher information density per cell than digital memory
- Direct analog voltage storage
- Enables efficient FIR filters and moving averages
- No conversion overhead
Technical Advantages
Information Density:
Storage Type:
Real-World Applications
Marine Applications
Long-duration underwater missions with 10³x energy reduction compared to digital solutions.
Key Applications:
- Active sonar echolocation with real-time object classification
- Biological-inspired acoustic pattern analysis
- Underwater monitoring systems
Space Systems
30% reduction in electronic mass and 60% reduction in coolant mass for satellites.
Key Applications:
- Attitude control with 0.2 Nm torque resolution
- Solar panel optimization with 10¹⁰x energy efficiency
- Adaptive signal modulation for LEO constellations
- In-memory RF beamforming for Ka-band communications
Automotive ADAS
Millisecond reaction times for Advanced Driver-Assistance Systems.
Key Applications:
- Real-time object detection and recognition
- Enhanced radar sensor capabilities
- LiDAR processing with 30% extended range
- Real-time 3D mapping
Security & IoT
Low-power sensor nodes with instantaneous alert mechanisms.
Key Applications:
- Industrial surveillance systems
- IoT ecosystem monitoring
- Edge computing applications
- Continuous environmental monitoring
ONNX Compatibility & Workflow Tools
Seamless integration with existing AI workflows
ANNET is fully compatible with ONNX (Open Neural Network Exchange), enabling easy conversion of existing digital neural network models from PyTorch, TensorFlow, and other popular frameworks into ANNET-compatible analog structures.
Automated model conversion
Analog structure generation
Configuration file creation