# Perception Stack

> Sensor hardware, deep-learning math, and navigation systems.


## Posts

- [A Kalman Update From GPS And Motion](https://perceptionstack.dev/a-kalman-update-from-gps-and-motion/): An IMU can carry a position estimate between GPS fixes, but its errors accumulate. A one-dimensional worked example shows how a Kalman update combines an uncertain prediction with a noisier-or-better measurement, and where the assumptions enter.
- [What Cross-Entropy Teaches a Classifier](https://perceptionstack.dev/what-cross-entropy-teaches-a-classifier/): A classifier’s raw scores are not probabilities, and cross-entropy does more than reward the right answer. A small three-class example shows how logits become a loss and what its gradient asks the model to change.
- [From Camera Pixels to a 3D Ray](https://perceptionstack.dev/from-camera-pixels-to-a-3d-ray/): A pixel coordinate is not a direction until you account for focal length, the principal point, and the camera’s coordinate frame. Work through the conversion, then see where lens distortion changes the result.

## Pages

- [About](https://perceptionstack.dev/about/)
- [Blog](https://perceptionstack.dev/blog/)
- [Home](https://perceptionstack.dev/)
- [GNC ∩ Deep Learning](https://perceptionstack.dev/tutorials/): Derivations, measured results and browser-native simulations across guidance/navigation/control, deep-learning perception models, and the sensors and compute that connect them to the physical world.


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