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+What are the resulting graphs from convolution and correlation?
+
+As the distance towards an object approaches infinity, its binocular disparity approaches zero.
+
+Which of the following are reasons why the huaman visual system relies on processing binocular disapairy?
+	- It supports accurate depth perception Yes
+	- It enables steerospic 3D vision Yes
+	- It aids in motion planning and interaction with objects such as reaching and grasping Yes
+	- It enhances colour discrimination and sharpens visual activity Yes
+	- It contributes to sound localisation through visual spatial integration Yes
+
+What is a key advantage of using phase-based methods compared to traditional window-based cross-correlation?
+	- Phase-based methods allow for faster and more biological plausible computation of image disparity Yes
+	- Phase-based methods completly remove noise from the image data Yes/No
+	- No, window-based cross-corrleation is preferred because it is computatinally more efficient No
+	- phase-based mehtods require no infrmation about local image structure No
+
+What are corrleations (cross or auto) used for
+	- Determining the temporal relation between cell firing Yes
+	- Measuring the self- similarity of cell firing Yes
+	- Descritoi of network operation ssuch sas lateral inhibition No
+	- Modeling tempral filter charactreristics of membranes No
+	- Measuring the strenght of cell-to-cell connections Yes
+	
+Select the correct statements about correlation fucntions
+	- The correlation $h (x) =  g (x) * f (x)$ is equal to $f (x) * g (x)$ mirrored at the Y-Axis Yes
+	- Cross-correlation is sued to deterinme the spatioal realtion between two cells firing No
+	- Cross corellatoin are used b ythe brain to determine motin and soud perception aspects Yes
+	- Auto-correlatoin gives the similatity between bservations of a vairable and its time-shifted version Yes
+	- auto correltaions always have their maximum peak at t=0 Yes
+	- if the psike train has a period of tau then its autocorrletaio nfucntion ahs theirr maximum peak at $t =  tau$ No
+	- Auto corrletaion are approcimatley even functions Yes
+	- the presence of noise can overdamp the amplitude of the oscillations of a given autocorrleation function Yes
+	- auto correlations always show oscillatory patterns No
+
+Which crosscorrelatoin function represents to mutually activating neurons (activating each other)?
+