g processing systems are also still significantly dumber than humans when it comes to taking spatial decisions based on complex multichannel inputs. For example, a racing driver driving a Formula One car uses audio, visual, vibrational and wind speed information and a sense of smell in subtle and significant ways that are presently hard to replicate either in terms of capture bandwidth or information processing in artificial intelligence systems. However, leaving aside how audio and visual information is actually used, there are some areas where devices are better at 'seeing' the real world than we are. CCD and CMOS sensors for example are capable of capturing and processing photons well into the nonvisible infrared spectrum (up to 900 nanometres for CMOS and over 1000 nanometres for CCD) - the basis for present night-vision systems. There are similarities between the image processing chain and the RF processing chain. In RF signal processing, the three major system performance requirements are sensitivity (the ability to detect wanted signal energy in the presence of a noise floor), selectivity (the ability to detect wanted signal energy in the presence of interfering signals) and stability (the ability to achieve sensitivity and selectivity over time, temperature and a wide range of operating conditions). Noise is a composite of Gaussian white noise introduced by the devices used to process (filter and amplify) the signal and distortion with the added complication of nonlinear effects that create harmonic distortion. Image processing is very similar. The lens is the equivalent of the radio antenna but collects photons (radiant energy in the visible optical bands), rather than RF energy. 10.2 Radio Waves, Light Waves and the Mechanics of Information Transfer Radio waves are useable in terms of our ability to collect wanted energy from them from a few kHz (let's say 3 kHz) to 300 GHz, above which the atmosphere becomes to all intents and purposes completely opaque. Information-Centric Software In wavelength terms