DASDAF represents a significant improvement with respect to other classifiers and pattern analysis technologies.  Processing is done in three steps: (1) Agreement Map (AM) generation/fusion; (2) AM bitwise binary processing to remove isolated agreement events, fuse multiple training set exemplars related to the same or similar targets, etc.; (3) AM processing via ATR FIR filtering within the “pattern space.”  It is applicable to any sensor output that can be represented as a set of numerical values  regardless of sensor type, data structure or compression level. FEATURES BENEFITS   Exploits archival & real-time target attributes Supports embedded processing implementations Adapts dynamically and  learns from experience Employs highly efficient, parallel operations Discloses Pattern Matching Process & results Dynamically adaptive providing robustness in actual  applications Parallel application of multiple classifiers to accurately identify observations and patterns   Solves problems related to dynamic data fusion, automatic recognition and classification in multi-sensor data streams   Correct classifications are Immediately visible with errors readily detected About Dynamic Adaptive Sensor Data Fusion Examples of Dynamic Adaptive Data Fusion