"Shortwave Sportfishing" wrote ...

Not really.

Mathematically, in particular when building a truth table, any number
of inputs always resolve to two states - 1 and 0 (yes/no, true/false).
This is true for any number system actually no matter how it is
expressed. But I digress.

There are varying decision states in truth tables, but they still
resolve to 1 or 0.

In fact, if you combine varying states of NOT, OR, AND, NOR, NAND and
EOR and resolve their states, you always end up with either 1 or 0.

This is true for any given number of inputs.

So, in effect, almost all decisions, if proper rules of logic are
applied, are binary - yes/no, true/false.

Can't be any other way.


So... the answer to any math problem is either 1 or zero? ;-)

I thought that was only true of binary systems. What about inputs of 0.237, and
0.667-j.997? They can be quantized to 1's and zero's but that incurs
quantization error, a loss of information, and induces noise in the result.

I think the real issue in making binary decisions is whether the
sensors/quantizers have enough dynamic range and resolution. But I'm just an
old analog guy...

-rick-

"-rick-" wrote in message
...

"Shortwave Sportfishing" wrote ...

Not really.

Mathematically, in particular when building a truth table, any number
of inputs always resolve to two states - 1 and 0 (yes/no, true/false).
This is true for any number system actually no matter how it is
expressed. But I digress.

There are varying decision states in truth tables, but they still
resolve to 1 or 0.

In fact, if you combine varying states of NOT, OR, AND, NOR, NAND and
EOR and resolve their states, you always end up with either 1 or 0.

This is true for any given number of inputs.

So, in effect, almost all decisions, if proper rules of logic are
applied, are binary - yes/no, true/false.

Can't be any other way.


So... the answer to any math problem is either 1 or zero? ;-)

I thought that was only true of binary systems. What about inputs of
0.237, and 0.667-j.997? They can be quantized to 1's and zero's but that
incurs quantization error, a loss of information, and induces noise in the
result.

I think the real issue in making binary decisions is whether the
sensors/quantizers have enough dynamic range and resolution. But I'm just
an old analog guy...

-rick-


There is error in your 0.667. Is it 0.6666 or 0.6674? Noise is introduced
where you keep more than 3 decimal points of answer.

On Mon, 3 Oct 2005 20:17:38 -0700, "-rick-" wrote:


"Shortwave Sportfishing" wrote ...

Not really.

Mathematically, in particular when building a truth table, any number
of inputs always resolve to two states - 1 and 0 (yes/no, true/false).
This is true for any number system actually no matter how it is
expressed. But I digress.

There are varying decision states in truth tables, but they still
resolve to 1 or 0.

In fact, if you combine varying states of NOT, OR, AND, NOR, NAND and
EOR and resolve their states, you always end up with either 1 or 0.

This is true for any given number of inputs.

So, in effect, almost all decisions, if proper rules of logic are
applied, are binary - yes/no, true/false.

Can't be any other way.


So... the answer to any math problem is either 1 or zero? ;-)

I thought that was only true of binary systems. What about inputs of 0.237, and
0.667-j.997? They can be quantized to 1's and zero's but that incurs
quantization error, a loss of information, and induces noise in the result.

I think the real issue in making binary decisions is whether the
sensors/quantizers have enough dynamic range and resolution. But I'm just an
old analog guy...

-rick-





No one has said the solution to a math problem is either 1 or 0.

--
John H.

"Divide each difficulty into as many parts as is feasible and necessary to resolve it."
Rene Descartes