For one wedge, the worst case is a monotonic signal, which will saturate
the wedge with R samples.

For two wedges, the worst case is the situation where the absolute distance
from previous samples to the latest sample is monotonically decreasing.  In
this case the wedges will contain R+1 samples between them (because the
latest sample always appears in both).

– Evan Balster
creator of imitone <http://imitone.com>

On Fri, Sep 2, 2016 at 12:36 PM, Ethan Duni <ethan.d...@gmail.com> wrote:

> Right aren't monotonic signals the worst case here? Or maybe not, since
> they're worst for one wedge, but best for the other?
>
> Ethan D
>
> On Fri, Sep 2, 2016 at 10:12 AM, Evan Balster <e...@imitone.com> wrote:
>
>> Just a few clarifications:
>>
>> - Local maxima and first difference don't really matter.  The maximum
>> wedge describes global maxima for all intervals [t-x, t], where x=[R-1..0].
>>
>> - If two equal samples are encountered, the algorithm can forget about
>> the older of them.
>>
>> It has been very helpful for my purposes to visualize the algorithm thus:
>>  Imagine drawing lines rightward from all points on the signal.  Those
>> which extend to the present time without intersecting other parts of the
>> signal form the minimum and maximum wedge.  The newest sample, and only the
>> newest sample, exists in both wedges.
>>
>> [image: Inline image 3]
>> http://interactopia.com/archive/images/lemire_algorithm.png
>>
>> The algorithm can safely forget anything in grey because it has been
>> "shadowed" by newer maximum or minimum values.
>>
>> – Evan Balster
>> creator of imitone <http://imitone.com>
>>
>> On Fri, Sep 2, 2016 at 1:50 AM, Ross Bencina <rossb-li...@audiomulch.com>
>> wrote:
>>
>>> On 2/09/2016 4:37 PM, Ross Bencina wrote:
>>>
>>>> When the first difference is positive, the history is trimmed. This is
>>>> the only time any kind of O(N) or O(log2(N)) operation is performed.
>>>> First difference positive implies that a new local maximum is achieved:
>>>> in this case, all of the most recent history samples that are less than
>>>> the new maximum are trimmed.
>>>>
>>>
>>> Correction:
>>>
>>> [The new local maximum dominates all
>>>> history up to the most recent *history sample* that exceeds it, which is
>>>> retained.]
>>>>
>>>
>>> I had said "most recent local maximum" but the history contains a
>>> monotonic non-increasing sequence.
>>>
>>> Ross.
>>>
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>>>
>>
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